xuning / sherpaonnx

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Fangjun Kuang
Committed by GitHub
c3a2e8a6 1 parent c7691650

Refactor Java API (#806)

内嵌 并排对比
正在显示 42 个修改的文件 包含 1004 行增加 和 964 行删除
... ... @@ -11,6 +11,7 @@ on:
- 'java-api-examples/**'
- 'sherpa-onnx/csrc/*'
- 'sherpa-onnx/jni/*'
- 'sherpa-onnx/java-api/**'
pull_request:
branches:
- master
... ... @@ -21,6 +22,7 @@ on:
- 'java-api-examples/**'
- 'sherpa-onnx/csrc/*'
- 'sherpa-onnx/jni/*'
- 'sherpa-onnx/java-api/**'
workflow_dispatch:
concurrency:
... ... @@ -46,7 +48,7 @@ jobs:
- name: ccache
uses: hendrikmuhs/ccache-action@v1.2
with:
key: ${{ matrix.os }}
key: ${{ matrix.os }}-java
- name: Display java version
shell: bash
... ... @@ -54,6 +56,42 @@ jobs:
java -version
echo "JAVA_HOME is: ${JAVA_HOME}"
cmake --version
- name: Build sherpa-onnx (jar)
shell: bash
run: |
cd sherpa-onnx/java-api/
make
ls -lh
- uses: actions/upload-artifact@v4
with:
name: sherpa-onnx-jar-${{ matrix.os }}
path: sherpa-onnx/java-api/build
- name: Build sherpa-onnx (C++)
shell: bash
run: |
export CMAKE_CXX_COMPILER_LAUNCHER=ccache
export PATH="/usr/lib/ccache:/usr/local/opt/ccache/libexec:$PATH"
mkdir build
cd build
cmake \
-DSHERPA_ONNX_ENABLE_PYTHON=OFF \
-DSHERPA_ONNX_ENABLE_TESTS=OFF \
-DSHERPA_ONNX_ENABLE_CHECK=OFF \
-DBUILD_SHARED_LIBS=ON \
-DSHERPA_ONNX_ENABLE_PORTAUDIO=OFF \
-DSHERPA_ONNX_ENABLE_BINARY=OFF \
-DSHERPA_ONNX_ENABLE_JNI=ON \
..
make -j4
ls -lh lib
- name: Run java test
shell: bash
run: |
... ... @@ -62,4 +100,12 @@ jobs:
cmake --version
cd ./java-api-examples
./runtest.sh
./run-streaming-decode-file-ctc.sh
# Delete model files to save space
rm -rf sherpa-onnx-streaming-*
./run-streaming-decode-file-paraformer.sh
rm -rf sherpa-onnx-streaming-*
./run-streaming-decode-file-transducer.sh
rm -rf sherpa-onnx-streaming-*
... ...
... ... @@ -66,11 +66,11 @@ jobs:
- os: macos-14
python-version: "3.12"
- os: windows-2019
- os: windows-2022
python-version: "3.7"
- os: windows-2019
- os: windows-2022
python-version: "3.8"
- os: windows-2019
- os: windows-2022
python-version: "3.9"
- os: windows-2022
... ...
lib
hs_err*
!run-streaming*.sh
... ...
ENTRY_POINT = ./
LIB_SRC_DIR := ../sherpa-onnx/java-api/src/com/k2fsa/sherpa/onnx
LIB_FILES = \
$(LIB_SRC_DIR)/EndpointRule.java \
$(LIB_SRC_DIR)/EndpointConfig.java \
$(LIB_SRC_DIR)/FeatureConfig.java \
$(LIB_SRC_DIR)/OnlineLMConfig.java \
$(LIB_SRC_DIR)/OnlineTransducerModelConfig.java \
$(LIB_SRC_DIR)/OnlineParaformerModelConfig.java \
$(LIB_SRC_DIR)/OnlineZipformer2CtcModelConfig.java \
$(LIB_SRC_DIR)/OnlineModelConfig.java \
$(LIB_SRC_DIR)/OnlineRecognizerConfig.java \
$(LIB_SRC_DIR)/OnlineStream.java \
$(LIB_SRC_DIR)/OnlineRecognizer.java
WEBSOCKET_DIR:= ./src/websocketsrv
WEBSOCKET_FILES = \
$(WEBSOCKET_DIR)/ConnectionData.java \
$(WEBSOCKET_DIR)/DecoderThreadHandler.java \
$(WEBSOCKET_DIR)/StreamThreadHandler.java \
$(WEBSOCKET_DIR)/AsrWebsocketServer.java \
$(WEBSOCKET_DIR)/AsrWebsocketClient.java \
LIB_BUILD_DIR = ./lib
EXAMPLE_FILE = DecodeFile.java
EXAMPLE_Mic = DecodeMic.java
JAVAC = javac
BUILD_DIR = build
RUNJFLAGS = -Dfile.encoding=utf-8
vpath %.class $(BUILD_DIR)
vpath %.java src
buildfile:
$(JAVAC) -cp lib/sherpaonnx.jar -d $(BUILD_DIR) -encoding UTF-8 src/$(EXAMPLE_FILE)
buildmic:
$(JAVAC) -cp lib/sherpaonnx.jar -d $(BUILD_DIR) -encoding UTF-8 src/$(EXAMPLE_Mic)
rebuild: clean all
.PHONY: clean run downjar
downjar:
wget https://repo1.maven.org/maven2/org/slf4j/slf4j-api/1.7.25/slf4j-api-1.7.25.jar -P ./lib/
wget https://repo1.maven.org/maven2/org/slf4j/slf4j-simple/1.7.25/slf4j-simple-1.7.25.jar -P ./lib/
wget https://github.com/TooTallNate/Java-WebSocket/releases/download/v1.5.3/Java-WebSocket-1.5.3.jar -P ./lib/
clean:
rm -frv $(BUILD_DIR)/*
rm -frv $(LIB_BUILD_DIR)/*
mkdir -p $(BUILD_DIR)
mkdir -p ./lib
runfile: packjar buildfile
java -cp ./lib/sherpaonnx.jar:build $(RUNJFLAGS) DecodeFile test.wav
runhotwords:
java -cp ./lib/sherpaonnx.jar:build $(RUNJFLAGS) DecodeFile hotwords.wav
runmic:
java -cp ./lib/sherpaonnx.jar:build $(RUNJFLAGS) DecodeMic
runsrv:
java -cp $(BUILD_DIR):lib/Java-WebSocket-1.5.3.jar:lib/slf4j-simple-1.7.25.jar:lib/slf4j-api-1.7.25.jar:../lib/sherpaonnx.jar $(RUNJFLAGS) websocketsrv.AsrWebsocketServer $(shell pwd)/../build/lib/libsherpa-onnx-jni.so ./modeltest.cfg
runclient:
java -cp $(BUILD_DIR):lib/Java-WebSocket-1.5.3.jar:lib/slf4j-simple-1.7.25.jar:lib/slf4j-api-1.7.25.jar:../lib/sherpaonnx.jar $(RUNJFLAGS) websocketsrv.AsrWebsocketClient $(shell pwd)/../build/lib/libsherpa-onnx-jni.so 127.0.0.1 8890 ./test.wav 32
runclienthotwords:
java -cp $(BUILD_DIR):lib/Java-WebSocket-1.5.3.jar:lib/slf4j-simple-1.7.25.jar:lib/slf4j-api-1.7.25.jar:../lib/sherpaonnx.jar $(RUNJFLAGS) websocketsrv.AsrWebsocketClient $(shell pwd)/../build/lib/libsherpa-onnx-jni.so 127.0.0.1 8890 ./hotwords.wav 32
buildlib: $(LIB_FILES:.java=.class)
%.class: %.java
$(JAVAC) -cp $(BUILD_DIR) -d $(BUILD_DIR) -encoding UTF-8 $<
buildwebsocket: $(WEBSOCKET_FILES:.java=.class)
%.class: %.java
$(JAVAC) -cp $(BUILD_DIR):lib/slf4j-simple-1.7.25.jar:lib/slf4j-api-1.7.25.jar:lib/Java-WebSocket-1.5.3.jar:../lib/sherpaonnx.jar -d $(BUILD_DIR) -encoding UTF-8 $<
packjar: buildlib
jar cvfe lib/sherpaonnx.jar . -C $(BUILD_DIR) .
all: clean buildlib packjar buildfile buildmic downjar buildwebsocket
0.Introduction
--------------
# Introduction
Java wrapper `com.k2fsa.sherpa.onnx.OnlineRecognizer` for `sherpa-onnx`. Java is a cross-platform language; you can build jni .so lib according to your system, and then use the same java api for all your platform.
now support multiple threads for websocket server
This directory contains examples for the JAVA API of sherpa-onnx.
```xml
Depend on:
Openjdk 1.8
```
---
1.Compile libsherpa-onnx-jni.so
-------------------------------
Compile sherpa-onnx/jni/jni.cc according to your system.
Example for Ubuntu 18.04 LTS, Openjdk 1.8.0_362:
```xml
git clone https://github.com/k2-fsa/sherpa-onnx
cd sherpa-onnx
mkdir build
cd build
cmake -DCMAKE_BUILD_TYPE=Release -DBUILD_SHARED_LIBS=ON -DSHERPA_ONNX_ENABLE_JNI=ON ..
make -j6
```
---
2.Download asr model files
--------------------------
[click here for more detail](https://k2-fsa.github.io/sherpa/onnx/pretrained_models/index.html)
--------------------------
3.Config model config.cfg
-------------------------
/**change model path in config.cfg according to your env**/
```xml
#model config
sample_rate=16000
feature_dim=80
rule1_min_trailing_silence=2.4
rule2_min_trailing_silence=1.2
rule3_min_utterance_length=20
encoder=/sherpa-onnx/build/bin/sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20/encoder-epoch-99-avg-1.onnx
decoder=/sherpa-onnx/build/bin/sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20/decoder-epoch-99-avg-1.onnx
joiner=/sherpa-onnx/build/bin/sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20/joiner-epoch-99-avg-1.onnx
tokens=/sherpa-onnx/build/bin/sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20/tokens.txt
num_threads=4
enable_endpoint_detection=false
decoding_method=greedy_search
max_active_paths=4
#websocket server config
port=8890
#number of threads pool for network io
connection_thread_num=16
#number of threads pool for stream
stream_thread_num=16
#number of threads pool for decoder
decoder_thread_num=16
#size of streams for parallel decoding
parallel_decoder_num=16
#time(ms) idle for decoder thread when no job
decoder_time_idle=10
#time(ms) out for connection data
deocder_time_out=3000
```
# Usage
---
4.A simple java example
-----------------------
refer to [java_api_example](https://github.com/k2-fsa/sherpa-onnx/blob/master/java-api-examples/src/DecodeFile.java) for more detail.
```java
import com.k2fsa.sherpa.onnx.OnlineRecognizer;
import com.k2fsa.sherpa.onnx.OnlineStream;
String cfgpath=appdir+"/modelconfig.cfg";
OnlineRecognizer.setSoPath(soPath); //set so lib path
OnlineRecognizer rcgOjb = new OnlineRecognizer(); //create a recognizer
rcgOjb = new OnlineRecognizer(cfgFile); //set model config file
CreateStream streamObj=rcgOjb.CreateStream(); //create a stream for read wav data
float[] buffer = rcgOjb.readWavFile(wavfilename); // read data from file
streamObj.acceptWaveform(buffer); // feed stream with data
streamObj.inputFinished(); // tell engine you done with all data
OnlineStream ssObj[] = new OnlineStream[1];
while (rcgOjb.isReady(streamObj)) { // engine is ready for unprocessed data
ssObj[0] = streamObj;
rcgOjb.decodeStreams(ssObj); // decode for multiple stream
// rcgOjb.DecodeStream(streamObj); // decode for single stream
}
String recText = "simple:" + rcgOjb.getResult(streamObj) + "\n";
byte[] utf8Data = recText.getBytes(StandardCharsets.UTF_8);
System.out.println(new String(utf8Data));
rcgOjb.reSet(streamObj);
rcgOjb.releaseStream(streamObj); // release stream
rcgOjb.release(); // release recognizer
```
---
5.Makefile
----------
OS Ubuntu 18.04 LTS
Build package path: /sherpa-onnx/java-api-examples/lib/sherpaonnx.jar
5.1 Build
```bash
cd sherpa-onnx/java-api-examples
make all
./run-streaming-decode-file-ctc.sh
./run-streaming-decode-file-paraformer.sh
./run-streaming-decode-file-transducer.sh
```
5.2 Run DecodeFile example
```bash
make runfile
```
5.3 Run DecodeMic example
```bash
make runmic
```
---
6.WebSocket Server
----------
support multiple threads for websocket server
6.0 Protocol for communication
1) client connect to server
```shell
ws client -> srv ws address
ws address example: ws://127.0.0.1:8889/
```
2) client send 16k pcm_s16le binary stream data to server
```shell
PCM sampleRate 16000
single channel
sampleSize 16bit
little endian
type short
```
3) client send "Done" text to server when all data is sent
```shell
ws_socket.send("Done")
```
4) client will receive json message from server whenever asr engine decoded new text
```shell
json example: {"text":"甚至出现交易几乎停滞的情况","eof":false"}
```
6.1 Build
```bash
cd sherpa-onnx/java-api-examples
make all
```
6.2 Run srv example
usage: AsrWebsocketServer soPath modelCfgPath
```bash
make runsrv /**change path in Makefile according to your env**/
```
6.3 Run multiple threads client example
usage: AsrWebsocketClient soPath srvIp srvPort wavPath numThreads
json result example: {"text":"甚至出现交易几乎停滞的情况","eof":"true"}
```bash
make runclient /**change path in Makefile according to your env**/
```
7 runtest
this script will download model, compile codes and run test
```bash
cd sherpa-onnx/java-api-examples
runtest.sh
```
\ No newline at end of file
... ...
// Copyright 2022-2023 by zhaoming
// Copyright 2024 Xiaomi Corporation
// This file shows how to use an online CTC model, i.e., streaming CTC model,
// to decode files.
import com.k2fsa.sherpa.onnx.*;
public class StreamingDecodeFileCtc {
public static void main(String[] args) {
// please refer to
// https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-streaming-zipformer-ctc-small-2024-03-18.tar.bz2
// to download model files
String model =
"./sherpa-onnx-streaming-zipformer-ctc-small-2024-03-18/ctc-epoch-30-avg-3-chunk-16-left-128.int8.onnx";
String tokens = "./sherpa-onnx-streaming-zipformer-ctc-small-2024-03-18/tokens.txt";
String waveFilename = "./sherpa-onnx-streaming-zipformer-ctc-small-2024-03-18/test_wavs/8k.wav";
WaveReader reader = new WaveReader(waveFilename);
System.out.println(reader.getSampleRate());
System.out.println(reader.getSamples().length);
OnlineZipformer2CtcModelConfig ctc =
OnlineZipformer2CtcModelConfig.builder().setModel(model).build();
OnlineModelConfig modelConfig =
OnlineModelConfig.builder()
.setZipformer2Ctc(ctc)
.setTokens(tokens)
.setNumThreads(1)
.setDebug(true)
.build();
OnlineRecognizerConfig config =
OnlineRecognizerConfig.builder()
.setOnlineModelConfig(modelConfig)
.setDecodingMethod("greedy_search")
.build();
OnlineRecognizer recognizer = new OnlineRecognizer(config);
OnlineStream stream = recognizer.createStream();
stream.acceptWaveform(reader.getSamples(), reader.getSampleRate());
float[] tailPaddings = new float[(int) (0.3 * reader.getSampleRate())];
stream.acceptWaveform(tailPaddings, reader.getSampleRate());
while (recognizer.isReady(stream)) {
recognizer.decode(stream);
}
String text = recognizer.getResult(stream).getText();
System.out.printf("filename:%s\nresult:%s\n", waveFilename, text);
stream.release();
recognizer.release();
}
}
... ...
// Copyright 2022-2023 by zhaoming
// Copyright 2024 Xiaomi Corporation
// This file shows how to use an online paraformer, i.e., streaming paraformer,
// to decode files.
import com.k2fsa.sherpa.onnx.*;
public class StreamingDecodeFileParaformer {
public static void main(String[] args) {
// please refer to
// https://k2-fsa.github.io/sherpa/onnx/pretrained_models/online-paraformer/paraformer-models.html#csukuangfj-sherpa-onnx-streaming-paraformer-bilingual-zh-en-chinese-english
// to download model files
String encoder = "./sherpa-onnx-streaming-paraformer-bilingual-zh-en/encoder.int8.onnx";
String decoder = "./sherpa-onnx-streaming-paraformer-bilingual-zh-en/decoder.int8.onnx";
String tokens = "./sherpa-onnx-streaming-paraformer-bilingual-zh-en/tokens.txt";
String waveFilename = "./sherpa-onnx-streaming-paraformer-bilingual-zh-en/test_wavs/2.wav";
WaveReader reader = new WaveReader(waveFilename);
System.out.println(reader.getSampleRate());
System.out.println(reader.getSamples().length);
OnlineParaformerModelConfig paraformer =
OnlineParaformerModelConfig.builder().setEncoder(encoder).setDecoder(decoder).build();
OnlineModelConfig modelConfig =
OnlineModelConfig.builder()
.setParaformer(paraformer)
.setTokens(tokens)
.setNumThreads(1)
.setDebug(true)
.build();
OnlineRecognizerConfig config =
OnlineRecognizerConfig.builder()
.setOnlineModelConfig(modelConfig)
.setDecodingMethod("greedy_search")
.build();
OnlineRecognizer recognizer = new OnlineRecognizer(config);
OnlineStream stream = recognizer.createStream();
stream.acceptWaveform(reader.getSamples(), reader.getSampleRate());
float[] tailPaddings = new float[(int) (0.8 * reader.getSampleRate())];
stream.acceptWaveform(tailPaddings, reader.getSampleRate());
while (recognizer.isReady(stream)) {
recognizer.decode(stream);
}
String text = recognizer.getResult(stream).getText();
System.out.printf("filename:%s\nresult:%s\n", waveFilename, text);
stream.release();
recognizer.release();
}
}
... ...
// Copyright 2022-2023 by zhaoming
// Copyright 2024 Xiaomi Corporation
// This file shows how to use an online transducer, i.e., streaming transducer,
// to decode files.
import com.k2fsa.sherpa.onnx.*;
public class StreamingDecodeFileTransducer {
public static void main(String[] args) {
// please refer to
// https://k2-fsa.github.io/sherpa/onnx/pretrained_models/online-transducer/zipformer-transducer-models.html#csukuangfj-sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20-bilingual-chinese-english
// to download model files
String encoder =
"./sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20/encoder-epoch-99-avg-1.int8.onnx";
String decoder =
"./sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20/decoder-epoch-99-avg-1.onnx";
String joiner =
"./sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20/joiner-epoch-99-avg-1.onnx";
String tokens = "./sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20/tokens.txt";
String waveFilename =
"./sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20/test_wavs/0.wav";
WaveReader reader = new WaveReader(waveFilename);
System.out.println(reader.getSampleRate());
System.out.println(reader.getSamples().length);
OnlineTransducerModelConfig transducer =
OnlineTransducerModelConfig.builder()
.setEncoder(encoder)
.setDecoder(decoder)
.setJoiner(joiner)
.build();
OnlineModelConfig modelConfig =
OnlineModelConfig.builder()
.setTransducer(transducer)
.setTokens(tokens)
.setNumThreads(1)
.setDebug(true)
.build();
OnlineRecognizerConfig config =
OnlineRecognizerConfig.builder()
.setOnlineModelConfig(modelConfig)
.setDecodingMethod("greedy_search")
.build();
OnlineRecognizer recognizer = new OnlineRecognizer(config);
OnlineStream stream = recognizer.createStream();
stream.acceptWaveform(reader.getSamples(), reader.getSampleRate());
float[] tailPaddings = new float[(int) (0.8 * reader.getSampleRate())];
stream.acceptWaveform(tailPaddings, reader.getSampleRate());
while (recognizer.isReady(stream)) {
recognizer.decode(stream);
}
String text = recognizer.getResult(stream).getText();
System.out.printf("filename:%s\nresult:%s\n", waveFilename, text);
stream.release();
recognizer.release();
}
}
... ...
#model config
sample_rate=16000
feature_dim=80
rule1_min_trailing_silence=2.4
rule2_min_trailing_silence=1.2
rule3_min_utterance_length=20
encoder=/sherpa/sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20/encoder-epoch-99-avg-1.onnx
decoder=/sherpa/sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20/decoder-epoch-99-avg-1.onnx
joiner=/sherpa/sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20/joiner-epoch-99-avg-1.onnx
tokens=/sherpa/sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20/tokens.txt
num_threads=4
enable_endpoint_detection=true
decoding_method=modified_beam_search
max_active_paths=4
hotwords_file=
hotwords_score=1.5
lm_model=
lm_scale=0.5
model_type=zipformer
#websocket server config
port=8890
connection_thread_num=16
stream_thread_num=16
decoder_thread_num=16
parallel_decoder_num=16
decoder_time_idle=200
deocder_time_out=30000
#!/usr/bin/env bash
set -ex
if [[ ! -f ../build/lib/libsherpa-onnx-jni.dylib && ! -f ../build/lib/libsherpa-onnx-jni.so ]]; then
mkdir -p ../build
pushd ../build
cmake \
-DSHERPA_ONNX_ENABLE_PYTHON=OFF \
-DSHERPA_ONNX_ENABLE_TESTS=OFF \
-DSHERPA_ONNX_ENABLE_CHECK=OFF \
-DBUILD_SHARED_LIBS=ON \
-DSHERPA_ONNX_ENABLE_PORTAUDIO=OFF \
-DSHERPA_ONNX_ENABLE_JNI=ON \
..
make -j4
ls -lh lib
popd
fi
if [ ! -f ../sherpa-onnx/java-api/build/sherpa-onnx.jar ]; then
pushd ../sherpa-onnx/java-api
make
popd
fi
if [ ! -f ./sherpa-onnx-streaming-zipformer-ctc-small-2024-03-18/tokens.txt ]; then
curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-streaming-zipformer-ctc-small-2024-03-18.tar.bz2
tar xvf sherpa-onnx-streaming-zipformer-ctc-small-2024-03-18.tar.bz2
rm sherpa-onnx-streaming-zipformer-ctc-small-2024-03-18.tar.bz2
fi
java \
-Djava.library.path=$PWD/../build/lib \
-cp ../sherpa-onnx/java-api/build/sherpa-onnx.jar \
StreamingDecodeFileCtc.java
... ...
#!/usr/bin/env bash
set -ex
if [[ ! -f ../build/lib/libsherpa-onnx-jni.dylib && ! -f ../build/lib/libsherpa-onnx-jni.so ]]; then
mkdir -p ../build
pushd ../build
cmake \
-DSHERPA_ONNX_ENABLE_PYTHON=OFF \
-DSHERPA_ONNX_ENABLE_TESTS=OFF \
-DSHERPA_ONNX_ENABLE_CHECK=OFF \
-DBUILD_SHARED_LIBS=ON \
-DSHERPA_ONNX_ENABLE_PORTAUDIO=OFF \
-DSHERPA_ONNX_ENABLE_JNI=ON \
..
make -j4
ls -lh lib
popd
fi
if [ ! -f ../sherpa-onnx/java-api/build/sherpa-onnx.jar ]; then
pushd ../sherpa-onnx/java-api
make
popd
fi
if [ ! -f ./sherpa-onnx-streaming-paraformer-bilingual-zh-en/tokens.txt ]; then
curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-streaming-paraformer-bilingual-zh-en.tar.bz2
tar xvf sherpa-onnx-streaming-paraformer-bilingual-zh-en.tar.bz2
rm sherpa-onnx-streaming-paraformer-bilingual-zh-en.tar.bz2
fi
java \
-Djava.library.path=$PWD/../build/lib \
-cp ../sherpa-onnx/java-api/build/sherpa-onnx.jar \
StreamingDecodeFileParaformer.java
... ...
#!/usr/bin/env bash
set -ex
if [[ ! -f ../build/lib/libsherpa-onnx-jni.dylib && ! -f ../build/lib/libsherpa-onnx-jni.so ]]; then
mkdir -p ../build
pushd ../build
cmake \
-DSHERPA_ONNX_ENABLE_PYTHON=OFF \
-DSHERPA_ONNX_ENABLE_TESTS=OFF \
-DSHERPA_ONNX_ENABLE_CHECK=OFF \
-DBUILD_SHARED_LIBS=ON \
-DSHERPA_ONNX_ENABLE_PORTAUDIO=OFF \
-DSHERPA_ONNX_ENABLE_JNI=ON \
..
make -j4
ls -lh lib
popd
fi
if [ ! -f ../sherpa-onnx/java-api/build/sherpa-onnx.jar ]; then
pushd ../sherpa-onnx/java-api
make
popd
fi
if [[ ! -f ../build/lib/libsherpa-onnx-jni.dylib && ! -f ../build/lib/libsherpa-onnx-jni.so ]]; then
cmake \
-DSHERPA_ONNX_ENABLE_PYTHON=OFF \
-DSHERPA_ONNX_ENABLE_TESTS=OFF \
-DSHERPA_ONNX_ENABLE_CHECK=OFF \
-DBUILD_SHARED_LIBS=ON \
-DSHERPA_ONNX_ENABLE_PORTAUDIO=OFF \
-DSHERPA_ONNX_ENABLE_JNI=ON \
..
make -j4
ls -lh lib
fi
if [ ! -f ./sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20/tokens.txt ]; then
curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20.tar.bz2
tar xvf sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20.tar.bz2
rm sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20.tar.bz2
fi
java \
-Djava.library.path=$PWD/../build/lib \
-cp ../sherpa-onnx/java-api/build/sherpa-onnx.jar \
StreamingDecodeFileTransducer.java
... ...
#!/usr/bin/env bash
#
# This scripts shows how to test java for sherpa-onnx
# Note: This scripts runs only on Linux and macOS
set -e
log() {
# This function is from espnet
local fname=${BASH_SOURCE[1]##*/}
echo -e "$(date '+%Y-%m-%d %H:%M:%S') (${fname}:${BASH_LINENO[0]}:${FUNCNAME[1]}) $*"
}
echo "PATH: $PATH"
log "------------------------------------------------------------"
log "Run download model"
log "------------------------------------------------------------"
repo_url=https://huggingface.co/csukuangfj/sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20
log "Start testing ${repo_url}"
repo=$(basename $repo_url)
log "download dir is $(basename $repo_url)"
if [ ! -d $repo ];then
log "Download pretrained model and test-data from $repo_url"
GIT_LFS_SKIP_SMUDGE=1 git clone $repo_url
pushd $repo
git lfs pull --include "*.onnx"
ls -lh *.onnx
popd
ln -s $repo/test_wavs/0.wav hotwords.wav
fi
log $(pwd)
sed -e 's?/sherpa/?'$(pwd)'/?g' modelconfig.cfg > modeltest.cfg
log "display model cfg"
cat modeltest.cfg
cd ..
export JAVA_HOME=$(readlink -f /usr/bin/javac | sed "s:/bin/javac::")
mkdir -p build
cd build
cmake -DCMAKE_BUILD_TYPE=Release -DBUILD_SHARED_LIBS=ON -DSHERPA_ONNX_ENABLE_JNI=ON ..
make -j4
ls -lh lib
export LD_LIBRARY_PATH=$PWD/build/lib:$LD_LIBRARY_PATH
cd ../java-api-examples
make all
make runfile
echo "礼 拜 二" > hotwords.txt
sed -i 's/hotwords_file=/hotwords_file=hotwords.txt/g' modeltest.cfg
make runhotwords
不能预览此文件类型
... ... @@ -6,11 +6,9 @@
set -ex
cd ..
mkdir -p build
cd build
if [[ ! -f ../build/lib/libsherpa-onnx-jni.dylib && ! -f ../build/lib/libsherpa-onnx-jni.so ]]; then
mkdir -p ../build
pushd ../build
cmake \
-DSHERPA_ONNX_ENABLE_PYTHON=OFF \
-DSHERPA_ONNX_ENABLE_TESTS=OFF \
... ... @@ -22,12 +20,11 @@ if [[ ! -f ../build/lib/libsherpa-onnx-jni.dylib && ! -f ../build/lib/libsherpa
make -j4
ls -lh lib
popd
fi
export LD_LIBRARY_PATH=$PWD/build/lib:$LD_LIBRARY_PATH
cd ../kotlin-api-examples
function testSpeakerEmbeddingExtractor() {
if [ ! -f ./3dspeaker_speech_eres2net_large_sv_zh-cn_3dspeaker_16k.onnx ]; then
curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/speaker-recongition-models/3dspeaker_speech_eres2net_large_sv_zh-cn_3dspeaker_16k.onnx
... ...
... ... @@ -253,7 +253,7 @@ int32_t main(int32_t argc, char *argv[]) {
sherpa_onnx::ReadWave(wave_filename, &actual_sample_rate, &is_ok);
if (!is_ok) {
SHERPA_ONNX_LOGE("Failed to read %s", wave_filename.c_str());
SHERPA_ONNX_LOGE("Failed to read '%s'", wave_filename.c_str());
return -1;
}
... ...
... ... @@ -96,7 +96,7 @@ static std::vector<std::vector<float>> ComputeEmbeddings(
sherpa_onnx::ReadWave(f, &sampling_rate, &is_ok);
if (!is_ok) {
fprintf(stderr, "Failed to read %s\n", f.c_str());
fprintf(stderr, "Failed to read '%s'\n", f.c_str());
exit(-1);
}
... ...
... ... @@ -78,7 +78,7 @@ for a list of pre-trained models to download.
sherpa_onnx::ReadWave(wav_filename, &sampling_rate, &is_ok);
if (!is_ok) {
fprintf(stderr, "Failed to read %s\n", wav_filename.c_str());
fprintf(stderr, "Failed to read '%s'\n", wav_filename.c_str());
return -1;
}
... ...
... ... @@ -93,7 +93,7 @@ static std::vector<std::vector<float>> ComputeEmbeddings(
sherpa_onnx::ReadWave(f, &sampling_rate, &is_ok);
if (!is_ok) {
fprintf(stderr, "Failed to read %s\n", f.c_str());
fprintf(stderr, "Failed to read '%s'\n", f.c_str());
exit(-1);
}
... ...
... ... @@ -58,7 +58,7 @@ for more models.
sherpa_onnx::ReadWave(wav_filename, &sampling_rate, &is_ok);
if (!is_ok) {
fprintf(stderr, "Failed to read %s\n", wav_filename.c_str());
fprintf(stderr, "Failed to read '%s'\n", wav_filename.c_str());
return -1;
}
... ...
... ... @@ -73,7 +73,7 @@ for a list of pre-trained models to download.
const std::vector<float> samples =
sherpa_onnx::ReadWave(wav_filename, &sampling_rate, &is_ok);
if (!is_ok) {
fprintf(stderr, "Failed to read %s\n", wav_filename.c_str());
fprintf(stderr, "Failed to read '%s'\n", wav_filename.c_str());
return -1;
}
float duration = samples.size() / static_cast<float>(sampling_rate);
... ...
... ... @@ -69,7 +69,7 @@ void AsrInference(const std::vector<std::vector<std::string>> &chunk_wav_paths,
const std::vector<float> samples =
sherpa_onnx::ReadWave(wav_filename, &sampling_rate, &is_ok);
if (!is_ok) {
fprintf(stderr, "Failed to read %s\n", wav_filename.c_str());
fprintf(stderr, "Failed to read '%s'\n", wav_filename.c_str());
continue;
}
duration += samples.size() / static_cast<float>(sampling_rate);
... ... @@ -96,7 +96,7 @@ void AsrInference(const std::vector<std::vector<std::string>> &chunk_wav_paths,
const std::vector<float> samples =
sherpa_onnx::ReadWave(wav_filename, &sampling_rate, &is_ok);
if (!is_ok) {
fprintf(stderr, "Failed to read %s\n", wav_filename.c_str());
fprintf(stderr, "Failed to read '%s'\n", wav_filename.c_str());
continue;
}
duration += samples.size() / static_cast<float>(sampling_rate);
... ...
... ... @@ -124,7 +124,7 @@ for a list of pre-trained models to download.
const std::vector<float> samples =
sherpa_onnx::ReadWave(wav_filename, &sampling_rate, &is_ok);
if (!is_ok) {
fprintf(stderr, "Failed to read %s\n", wav_filename.c_str());
fprintf(stderr, "Failed to read '%s'\n", wav_filename.c_str());
return -1;
}
duration += samples.size() / static_cast<float>(sampling_rate);
... ...
... ... @@ -109,7 +109,7 @@ for a list of pre-trained models to download.
sherpa_onnx::ReadWave(wav_filename, &sampling_rate, &is_ok);
if (!is_ok) {
fprintf(stderr, "Failed to read %s\n", wav_filename.c_str());
fprintf(stderr, "Failed to read '%s'\n", wav_filename.c_str());
return -1;
}
... ...
.idea
java-api.iml
out
META-INF
build
*.jar
... ...
# all .class and .jar files are put inside out_dir
out_dir := build
out_jar := $(out_dir)/sherpa-onnx.jar
package_dir := com/k2fsa/sherpa/onnx
java_files := WaveReader.java
java_files += EndpointRule.java
java_files += EndpointConfig.java
java_files += FeatureConfig.java
java_files += OnlineLMConfig.java
java_files += OnlineParaformerModelConfig.java
java_files += OnlineZipformer2CtcModelConfig.java
java_files += OnlineTransducerModelConfig.java
java_files += OnlineModelConfig.java
java_files += OnlineStream.java
java_files += OnlineRecognizerConfig.java
java_files += OnlineRecognizerResult.java
java_files += OnlineRecognizer.java
class_files := $(java_files:%.java=%.class)
java_files := $(addprefix src/$(package_dir)/,$(java_files))
class_files := $(addprefix $(out_dir)/$(package_dir)/,$(class_files))
$(info -- java files $(java_files))
$(info --)
$(info -- class files $(class_files))
.phony: all clean
all: $(out_jar)
$(out_jar): $(class_files)
jar --create --verbose --file $(out_jar) -C $(out_dir) .
clean:
$(RM) -rfv $(out_dir)
$(class_files): $(out_dir)/$(package_dir)/%.class: src/$(package_dir)/%.java
javac -d $(out_dir) --class-path $(out_dir) $<
... ...
/*
* // Copyright 2022-2023 by zhaoming
*/
// Copyright 2022-2023 by zhaoming
// Copyright 2024 Xiaomi Corporation
package com.k2fsa.sherpa.onnx;
public class EndpointConfig {
private final EndpointRule rule1;
private final EndpointRule rule2;
private final EndpointRule rule3;
public EndpointConfig(EndpointRule rule1, EndpointRule rule2, EndpointRule rule3) {
this.rule1 = rule1;
this.rule2 = rule2;
this.rule3 = rule3;
private EndpointConfig(Builder builder) {
this.rule1 = builder.rule1;
this.rule2 = builder.rule2;
this.rule3 = builder.rule3;
}
public static Builder builder() {
return new Builder();
}
public EndpointRule getRule1() {
... ... @@ -26,4 +30,42 @@ public class EndpointConfig {
public EndpointRule getRule3() {
return rule3;
}
public static class Builder {
private EndpointRule rule1 = EndpointRule.builder().
setMustContainNonSilence(false).
setMinTrailingSilence(2.4f).
setMinUtteranceLength(0).
build();
private EndpointRule rule2 = EndpointRule.builder().
setMustContainNonSilence(true).
setMinTrailingSilence(1.4f).
setMinUtteranceLength(0).
build();
private EndpointRule rule3 = EndpointRule.builder().
setMustContainNonSilence(false).
setMinTrailingSilence(0.0f).
setMinUtteranceLength(20.0f).
build();
public EndpointConfig build() {
return new EndpointConfig(this);
}
public Builder setRule1(EndpointRule rule) {
this.rule1 = rule;
return this;
}
public Builder setRule2(EndpointRule rule) {
this.rule2 = rule;
return this;
}
public Builder setRul3(EndpointRule rule) {
this.rule3 = rule;
return this;
}
}
}
... ...
/*
* // Copyright 2022-2023 by zhaoming
*/
// Copyright 2022-2023 by zhaoming
// Copyright 2024 Xiaomi Corporation
package com.k2fsa.sherpa.onnx;
public class EndpointRule {
private final boolean mustContainNonSilence;
private final float minTrailingSilence;
private final float minUtteranceLength;
public EndpointRule(
boolean mustContainNonSilence, float minTrailingSilence, float minUtteranceLength) {
this.mustContainNonSilence = mustContainNonSilence;
this.minTrailingSilence = minTrailingSilence;
this.minUtteranceLength = minUtteranceLength;
private EndpointRule(Builder builder) {
this.mustContainNonSilence = builder.mustContainNonSilence;
this.minTrailingSilence = builder.minTrailingSilence;
this.minUtteranceLength = builder.minUtteranceLength;
}
public static Builder builder() {
return new Builder();
}
public float getMinTrailingSilence() {
... ... @@ -27,4 +29,29 @@ public class EndpointRule {
public boolean getMustContainNonSilence() {
return mustContainNonSilence;
}
}
public static class Builder {
private boolean mustContainNonSilence = false;
private float minTrailingSilence = 0;
private float minUtteranceLength = 0;
public EndpointRule build() {
return new EndpointRule(this);
}
public Builder setMustContainNonSilence(boolean mustContainNonSilence) {
this.mustContainNonSilence = mustContainNonSilence;
return this;
}
public Builder setMinTrailingSilence(float minTrailingSilence) {
this.minTrailingSilence = minTrailingSilence;
return this;
}
public Builder setMinUtteranceLength(float minUtteranceLength) {
this.minUtteranceLength = minUtteranceLength;
return this;
}
}
}
\ No newline at end of file
... ...
/*
* // Copyright 2022-2023 by zhaoming
*/
// Copyright 2022-2023 by zhaoming
// Copyright 2024 Xiaomi Corporation
package com.k2fsa.sherpa.onnx;
... ... @@ -8,9 +7,13 @@ public class FeatureConfig {
private final int sampleRate;
private final int featureDim;
public FeatureConfig(int sampleRate, int featureDim) {
this.sampleRate = sampleRate;
this.featureDim = featureDim;
private FeatureConfig(Builder builder) {
this.sampleRate = builder.sampleRate;
this.featureDim = builder.featureDim;
}
public static Builder builder() {
return new Builder();
}
public int getSampleRate() {
... ... @@ -20,4 +23,23 @@ public class FeatureConfig {
public int getFeatureDim() {
return featureDim;
}
public static class Builder {
private int sampleRate = 16000;
private int featureDim = 80;
public FeatureConfig build() {
return new FeatureConfig(this);
}
public Builder setSampleRate(int sampleRate) {
this.sampleRate = sampleRate;
return this;
}
public Builder setFeatureDim(int featureDim) {
this.featureDim = featureDim;
return this;
}
}
}
... ...
/*
* // Copyright 2022-2023 by zhaoming
*/
// Copyright 2022-2023 by zhaoming
// Copyright 2024 Xiaomi Corporation
package com.k2fsa.sherpa.onnx;
public class OnlineLMConfig {
private final String model;
private final float scale;
public OnlineLMConfig(String model, float scale) {
this.model = model;
this.scale = scale;
private OnlineLMConfig(Builder builder) {
this.model = builder.model;
this.scale = builder.scale;
}
public static Builder builder() {
return new Builder();
}
public String getModel() {
... ... @@ -20,4 +24,23 @@ public class OnlineLMConfig {
public float getScale() {
return scale;
}
}
public static class Builder {
private String model = "";
private float scale = 1.0f;
public OnlineLMConfig build() {
return new OnlineLMConfig(this);
}
public Builder setModel(String model) {
this.model = model;
return this;
}
public Builder setScale(float scale) {
this.scale = scale;
return this;
}
}
}
\ No newline at end of file
... ...
/*
* // Copyright 2022-2023 by zhaoming
*/
// Copyright 2022-2023 by zhaoming
// Copyright 2024 Xiaomi Corporation
package com.k2fsa.sherpa.onnx;
public class OnlineModelConfig {
private final OnlineParaformerModelConfig paraformer;
private final OnlineTransducerModelConfig transducer;
private final OnlineParaformerModelConfig paraformer;
private final OnlineZipformer2CtcModelConfig zipformer2Ctc;
private final String tokens;
private final int numThreads;
private final boolean debug;
private final String provider = "cpu";
private String modelType = "";
public OnlineModelConfig(
String tokens,
int numThreads,
boolean debug,
String modelType,
OnlineParaformerModelConfig paraformer,
OnlineTransducerModelConfig transducer,
OnlineZipformer2CtcModelConfig zipformer2Ctc
) {
this.tokens = tokens;
this.numThreads = numThreads;
this.debug = debug;
this.modelType = modelType;
this.paraformer = paraformer;
this.transducer = transducer;
this.zipformer2Ctc = zipformer2Ctc;
private final String provider;
private final String modelType;
private OnlineModelConfig(Builder builder) {
this.transducer = builder.transducer;
this.paraformer = builder.paraformer;
this.zipformer2Ctc = builder.zipformer2Ctc;
this.tokens = builder.tokens;
this.numThreads = builder.numThreads;
this.debug = builder.debug;
this.provider = builder.provider;
this.modelType = builder.modelType;
}
public static Builder builder() {
return new Builder();
}
public OnlineParaformerModelConfig getParaformer() {
... ... @@ -41,6 +35,10 @@ public class OnlineModelConfig {
return transducer;
}
public OnlineZipformer2CtcModelConfig getZipformer2Ctc() {
return zipformer2Ctc;
}
public String getTokens() {
return tokens;
}
... ... @@ -52,4 +50,67 @@ public class OnlineModelConfig {
public boolean getDebug() {
return debug;
}
public String getProvider() {
return provider;
}
public String getModelType() {
return modelType;
}
public static class Builder {
private OnlineParaformerModelConfig paraformer = OnlineParaformerModelConfig.builder().build();
private OnlineTransducerModelConfig transducer = OnlineTransducerModelConfig.builder().build();
private OnlineZipformer2CtcModelConfig zipformer2Ctc = OnlineZipformer2CtcModelConfig.builder().build();
private String tokens = "";
private int numThreads = 1;
private boolean debug = true;
private String provider = "cpu";
private String modelType = "";
public OnlineModelConfig build() {
return new OnlineModelConfig(this);
}
public Builder setTransducer(OnlineTransducerModelConfig transducer) {
this.transducer = transducer;
return this;
}
public Builder setParaformer(OnlineParaformerModelConfig paraformer) {
this.paraformer = paraformer;
return this;
}
public Builder setZipformer2Ctc(OnlineZipformer2CtcModelConfig zipformer2Ctc) {
this.zipformer2Ctc = zipformer2Ctc;
return this;
}
public Builder setTokens(String tokens) {
this.tokens = tokens;
return this;
}
public Builder setNumThreads(int numThreads) {
this.numThreads = numThreads;
return this;
}
public Builder setDebug(boolean debug) {
this.debug = debug;
return this;
}
public Builder setProvider(String provider) {
this.provider = provider;
return this;
}
public Builder setModelType(String modelType) {
this.modelType = modelType;
return this;
}
}
}
... ...
/*
* // Copyright 2022-2023 by zhaoming
*/
// Copyright 2022-2023 by zhaoming
// Copyright 2024 Xiaomi Corporation
package com.k2fsa.sherpa.onnx;
... ... @@ -8,9 +7,13 @@ public class OnlineParaformerModelConfig {
private final String encoder;
private final String decoder;
public OnlineParaformerModelConfig(String encoder, String decoder) {
this.encoder = encoder;
this.decoder = decoder;
private OnlineParaformerModelConfig(Builder builder) {
this.encoder = builder.encoder;
this.decoder = builder.decoder;
}
public static Builder builder() {
return new Builder();
}
public String getEncoder() {
... ... @@ -20,4 +23,23 @@ public class OnlineParaformerModelConfig {
public String getDecoder() {
return decoder;
}
public static class Builder {
private String encoder = "";
private String decoder = "";
public OnlineParaformerModelConfig build() {
return new OnlineParaformerModelConfig(this);
}
public Builder setEncoder(String encoder) {
this.encoder = encoder;
return this;
}
public Builder setDecoder(String decoder) {
this.decoder = decoder;
return this;
}
}
}
... ...
/*
* // Copyright 2022-2023 by zhaoming
* // the online recognizer for sherpa-onnx, it can load config from a file
* // or by argument
*/
/*
usage example:
String cfgpath=appdir+"/modelconfig.cfg";
OnlineRecognizer.setSoPath(soPath); //set so lib path
OnlineRecognizer rcgOjb = new OnlineRecognizer(); //create a recognizer
rcgOjb = new OnlineRecognizer(cfgFile); //set model config file
CreateStream streamObj=rcgOjb.CreateStream(); //create a stream for read wav data
float[] buffer = rcgOjb.readWavFile(wavfilename); // read data from file
streamObj.acceptWaveform(buffer); // feed stream with data
streamObj.inputFinished(); // tell engine you done with all data
OnlineStream ssObj[] = new OnlineStream[1];
while (rcgOjb.isReady(streamObj)) { // engine is ready for unprocessed data
ssObj[0] = streamObj;
rcgOjb.decodeStreams(ssObj); // decode for multiple stream
// rcgOjb.DecodeStream(streamObj); // decode for single stream
}
String recText = "simple:" + rcgOjb.getResult(streamObj) + "\n";
byte[] utf8Data = recText.getBytes(StandardCharsets.UTF_8);
System.out.println(new String(utf8Data));
rcgOjb.reSet(streamObj);
rcgOjb.releaseStream(streamObj); // release stream
rcgOjb.release(); // release recognizer
*/
// Copyright 2022-2023 by zhaoming
// Copyright 2024 Xiaomi Corporation
package com.k2fsa.sherpa.onnx;
import java.io.BufferedInputStream;
import java.io.File;
import java.io.FileInputStream;
import java.io.InputStream;
import java.util.Enumeration;
import java.util.HashMap;
import java.util.Map;
import java.util.Properties;
public class OnlineRecognizer {
private long ptr = 0; // this is the asr engine ptrss
private int sampleRate = 16000;
// load config file for OnlineRecognizer
public OnlineRecognizer(String modelCfgPath) {
Map<String, String> proMap = this.readProperties(modelCfgPath);
try {
int sampleRate = Integer.parseInt(proMap.getOrDefault("sample_rate", "16000").trim());
this.sampleRate = sampleRate;
EndpointRule rule1 =
new EndpointRule(
false,
Float.parseFloat(proMap.getOrDefault("rule1_min_trailing_silence", "2.4").trim()),
0.0F);
EndpointRule rule2 =
new EndpointRule(
true,
Float.parseFloat(proMap.getOrDefault("rule2_min_trailing_silence", "1.2").trim()),
0.0F);
EndpointRule rule3 =
new EndpointRule(
false,
0.0F,
Float.parseFloat(proMap.getOrDefault("rule3_min_utterance_length", "20").trim()));
EndpointConfig endCfg = new EndpointConfig(rule1, rule2, rule3);
OnlineParaformerModelConfig modelParaCfg =
new OnlineParaformerModelConfig(
proMap.getOrDefault("encoder", "").trim(), proMap.getOrDefault("decoder", "").trim());
OnlineTransducerModelConfig modelTranCfg =
new OnlineTransducerModelConfig(
proMap.getOrDefault("encoder", "").trim(),
proMap.getOrDefault("decoder", "").trim(),
proMap.getOrDefault("joiner", "").trim());
OnlineZipformer2CtcModelConfig zipformer2CtcConfig = new OnlineZipformer2CtcModelConfig("");
OnlineModelConfig modelCfg =
new OnlineModelConfig(
proMap.getOrDefault("tokens", "").trim(),
Integer.parseInt(proMap.getOrDefault("num_threads", "4").trim()),
false,
proMap.getOrDefault("model_type", "zipformer").trim(),
modelParaCfg,
modelTranCfg, zipformer2CtcConfig);
FeatureConfig featConfig =
new FeatureConfig(
sampleRate, Integer.parseInt(proMap.getOrDefault("feature_dim", "80").trim()));
OnlineLMConfig onlineLmConfig =
new OnlineLMConfig(
proMap.getOrDefault("lm_model", "").trim(),
Float.parseFloat(proMap.getOrDefault("lm_scale", "0.5").trim()));
OnlineRecognizerConfig rcgCfg =
new OnlineRecognizerConfig(
featConfig,
modelCfg,
endCfg,
onlineLmConfig,
Boolean.parseBoolean(proMap.getOrDefault("enable_endpoint_detection", "true").trim()),
proMap.getOrDefault("decoding_method", "modified_beam_search").trim(),
Integer.parseInt(proMap.getOrDefault("max_active_paths", "4").trim()),
proMap.getOrDefault("hotwords_file", "").trim(),
Float.parseFloat(proMap.getOrDefault("hotwords_score", "1.5").trim()));
// create a new Recognizer, first parameter kept for android asset_manager ANDROID_API__ >= 9
this.ptr = createOnlineRecognizer(new Object(), rcgCfg);
} catch (Exception e) {
System.err.println(e);
}
static {
System.loadLibrary("sherpa-onnx-jni");
}
// use for android asset_manager ANDROID_API__ >= 9
public OnlineRecognizer(Object assetManager, String modelCfgPath) {
Map<String, String> proMap = this.readProperties(modelCfgPath);
try {
int sampleRate = Integer.parseInt(proMap.getOrDefault("sample_rate", "16000").trim());
this.sampleRate = sampleRate;
EndpointRule rule1 =
new EndpointRule(
false,
Float.parseFloat(proMap.getOrDefault("rule1_min_trailing_silence", "2.4").trim()),
0.0F);
EndpointRule rule2 =
new EndpointRule(
true,
Float.parseFloat(proMap.getOrDefault("rule2_min_trailing_silence", "1.2").trim()),
0.0F);
EndpointRule rule3 =
new EndpointRule(
false,
0.0F,
Float.parseFloat(proMap.getOrDefault("rule3_min_utterance_length", "20").trim()));
EndpointConfig endCfg = new EndpointConfig(rule1, rule2, rule3);
OnlineParaformerModelConfig modelParaCfg =
new OnlineParaformerModelConfig(
proMap.getOrDefault("encoder", "").trim(), proMap.getOrDefault("decoder", "").trim());
OnlineTransducerModelConfig modelTranCfg =
new OnlineTransducerModelConfig(
proMap.getOrDefault("encoder", "").trim(),
proMap.getOrDefault("decoder", "").trim(),
proMap.getOrDefault("joiner", "").trim());
OnlineZipformer2CtcModelConfig zipformer2CtcConfig = new OnlineZipformer2CtcModelConfig("");
OnlineModelConfig modelCfg =
new OnlineModelConfig(
proMap.getOrDefault("tokens", "").trim(),
Integer.parseInt(proMap.getOrDefault("num_threads", "4").trim()),
false,
proMap.getOrDefault("model_type", "zipformer").trim(),
modelParaCfg,
modelTranCfg, zipformer2CtcConfig);
FeatureConfig featConfig =
new FeatureConfig(
sampleRate, Integer.parseInt(proMap.getOrDefault("feature_dim", "80").trim()));
OnlineLMConfig onlineLmConfig =
new OnlineLMConfig(
proMap.getOrDefault("lm_model", "").trim(),
Float.parseFloat(proMap.getOrDefault("lm_scale", "0.5").trim()));
OnlineRecognizerConfig rcgCfg =
new OnlineRecognizerConfig(
featConfig,
modelCfg,
endCfg,
onlineLmConfig,
Boolean.parseBoolean(proMap.getOrDefault("enable_endpoint_detection", "true").trim()),
proMap.getOrDefault("decoding_method", "modified_beam_search").trim(),
Integer.parseInt(proMap.getOrDefault("max_active_paths", "4").trim()),
proMap.getOrDefault("hotwords_file", "").trim(),
Float.parseFloat(proMap.getOrDefault("hotwords_score", "1.5").trim()));
// create a new Recognizer, first parameter kept for android asset_manager ANDROID_API__ >= 9
this.ptr = createOnlineRecognizer(assetManager, rcgCfg);
private long ptr = 0; // this is the asr engine ptrss
} catch (Exception e) {
System.err.println(e);
}
}
// set onlineRecognizer by parameter
public OnlineRecognizer(
String tokens,
String encoder,
String decoder,
String joiner,
int numThreads,
int sampleRate,
int featureDim,
boolean enableEndpointDetection,
float rule1MinTrailingSilence,
float rule2MinTrailingSilence,
float rule3MinUtteranceLength,
String decodingMethod,
String lm_model,
float lm_scale,
int maxActivePaths,
String hotwordsFile,
float hotwordsScore,
String modelType) {
this.sampleRate = sampleRate;
EndpointRule rule1 = new EndpointRule(false, rule1MinTrailingSilence, 0.0F);
EndpointRule rule2 = new EndpointRule(true, rule2MinTrailingSilence, 0.0F);
EndpointRule rule3 = new EndpointRule(false, 0.0F, rule3MinUtteranceLength);
EndpointConfig endCfg = new EndpointConfig(rule1, rule2, rule3);
OnlineParaformerModelConfig modelParaCfg = new OnlineParaformerModelConfig(encoder, decoder);
OnlineTransducerModelConfig modelTranCfg =
new OnlineTransducerModelConfig(encoder, decoder, joiner);
OnlineZipformer2CtcModelConfig zipformer2CtcConfig = new OnlineZipformer2CtcModelConfig("");
OnlineModelConfig modelCfg =
new OnlineModelConfig(tokens, numThreads, false, modelType, modelParaCfg, modelTranCfg, zipformer2CtcConfig);
FeatureConfig featConfig = new FeatureConfig(sampleRate, featureDim);
OnlineLMConfig onlineLmConfig = new OnlineLMConfig(lm_model, lm_scale);
OnlineRecognizerConfig rcgCfg =
new OnlineRecognizerConfig(
featConfig,
modelCfg,
endCfg,
onlineLmConfig,
enableEndpointDetection,
decodingMethod,
maxActivePaths,
hotwordsFile,
hotwordsScore);
// create a new Recognizer, first parameter kept for android asset_manager ANDROID_API__ >= 9
this.ptr = createOnlineRecognizer(new Object(), rcgCfg);
public OnlineRecognizer(OnlineRecognizerConfig config) {
ptr = newFromFile(config);
}
/*
public static float[] readWavFile(String fileName) {
// read data from the filename
Object[] wavdata = readWave(fileName);
... ... @@ -238,139 +25,67 @@ public class OnlineRecognizer {
return floatData;
}
*/
// load the libsherpa-onnx-jni.so lib
public static void loadSoLib(String soPath) {
// load libsherpa-onnx-jni.so lib from the path
System.out.println("so lib path=" + soPath + "\n");
System.load(soPath.trim());
System.out.println("load so lib succeed\n");
}
public static void setSoPath(String soPath) {
OnlineRecognizer.loadSoLib(soPath);
OnlineStream.loadSoLib(soPath);
}
private static native Object[] readWave(String fileName); // static
private Map<String, String> readProperties(String modelCfgPath) {
// read and parse config file
Properties props = new Properties();
Map<String, String> proMap = new HashMap<>();
try {
File file = new File(modelCfgPath);
if (!file.exists()) {
System.out.println("model cfg file not exists!");
System.exit(0);
}
InputStream in = new BufferedInputStream(new FileInputStream(modelCfgPath));
props.load(in);
Enumeration en = props.propertyNames();
while (en.hasMoreElements()) {
String key = (String) en.nextElement();
String Property = props.getProperty(key);
proMap.put(key, Property);
}
} catch (Exception e) {
e.printStackTrace();
}
return proMap;
}
public void decodeStream(OnlineStream s) throws Exception {
if (this.ptr == 0) throw new Exception("null exception for recognizer ptr");
long streamPtr = s.getPtr();
if (streamPtr == 0) throw new Exception("null exception for stream ptr");
// when feeded samples to engine, call DecodeStream to let it process
decodeStream(this.ptr, streamPtr);
}
public void decodeStreams(OnlineStream[] ssOjb) throws Exception {
if (this.ptr == 0) throw new Exception("null exception for recognizer ptr");
// decode for multiple streams
long[] ss = new long[ssOjb.length];
for (int i = 0; i < ssOjb.length; i++) {
ss[i] = ssOjb[i].getPtr();
if (ss[i] == 0) throw new Exception("null exception for stream ptr");
}
decodeStreams(this.ptr, ss);
public void decode(OnlineStream s) {
decode(ptr, s.getPtr());
}
public boolean isReady(OnlineStream s) throws Exception {
// whether the engine is ready for decode
if (this.ptr == 0) throw new Exception("null exception for recognizer ptr");
long streamPtr = s.getPtr();
if (streamPtr == 0) throw new Exception("null exception for stream ptr");
return isReady(this.ptr, streamPtr);
}
public String getResult(OnlineStream s) throws Exception {
// get text from the engine
if (this.ptr == 0) throw new Exception("null exception for recognizer ptr");
long streamPtr = s.getPtr();
if (streamPtr == 0) throw new Exception("null exception for stream ptr");
return getResult(this.ptr, streamPtr);
public boolean isReady(OnlineStream s) {
return isReady(ptr, s.getPtr());
}
public boolean isEndpoint(OnlineStream s) throws Exception {
if (this.ptr == 0) throw new Exception("null exception for recognizer ptr");
long streamPtr = s.getPtr();
if (streamPtr == 0) throw new Exception("null exception for stream ptr");
return isEndpoint(this.ptr, streamPtr);
public boolean isEndpoint(OnlineStream s) {
return isEndpoint(ptr, s.getPtr());
}
public void reSet(OnlineStream s) throws Exception {
if (this.ptr == 0) throw new Exception("null exception for recognizer ptr");
long streamPtr = s.getPtr();
if (streamPtr == 0) throw new Exception("null exception for stream ptr");
reSet(this.ptr, streamPtr);
public void reset(OnlineStream s) {
reset(ptr, s.getPtr());
}
public OnlineStream createStream() throws Exception {
// create one stream for data to feed in
if (this.ptr == 0) throw new Exception("null exception for recognizer ptr");
long streamPtr = createStream(this.ptr);
OnlineStream stream = new OnlineStream(streamPtr, this.sampleRate);
return stream;
public OnlineStream createStream() {
long p = createStream(ptr, "");
return new OnlineStream(p);
}
@Override
protected void finalize() throws Throwable {
release();
}
// recognizer release, you'd better call it manually if not use anymore
public void release() {
if (this.ptr == 0) return;
deleteOnlineRecognizer(this.ptr);
if (this.ptr == 0) {
return;
}
delete(this.ptr);
this.ptr = 0;
}
// JNI interface libsherpa-onnx-jni.so
// stream release, you'd better call it manually if not use anymore
public void releaseStream(OnlineStream s) {
s.release();
public OnlineRecognizerResult getResult(OnlineStream s) {
Object[] arr = getResult(ptr, s.getPtr());
String text = (String) arr[0];
String[] tokens = (String[]) arr[1];
float[] timestamps = (float[]) arr[2];
return new OnlineRecognizerResult(text, tokens, timestamps);
}
private native String getResult(long ptr, long streamPtr);
private native void decodeStream(long ptr, long streamPtr);
private native void delete(long ptr);
private native void decodeStreams(long ptr, long[] ssPtr);
private native long newFromFile(OnlineRecognizerConfig config);
private native boolean isReady(long ptr, long streamPtr);
// first parameter keep for android asset_manager ANDROID_API__ >= 9
private native long createOnlineRecognizer(Object asset, OnlineRecognizerConfig config);
private native long createStream(long ptr, String hotwords);
private native long createStream(long ptr);
private native void reset(long ptr, long streamPtr);
private native void deleteOnlineRecognizer(long ptr);
private native void decode(long ptr, long streamPtr);
private native boolean isEndpoint(long ptr, long streamPtr);
private native void reSet(long ptr, long streamPtr);
}
private native boolean isReady(long ptr, long streamPtr);
private native Object[] getResult(long ptr, long streamPtr);
}
\ No newline at end of file
... ...
/*
* // Copyright 2022-2023 by zhaoming
*/
// Copyright 2022-2023 by zhaoming
// Copyright 2024 Xiaomi Corporation
package com.k2fsa.sherpa.onnx;
public class OnlineRecognizerConfig {
private final FeatureConfig featConfig;
private final OnlineModelConfig modelConfig;
private final EndpointConfig endpointConfig;
private final OnlineLMConfig lmConfig;
private final EndpointConfig endpointConfig;
private final boolean enableEndpoint;
private final String decodingMethod;
private final int maxActivePaths;
private final String hotwordsFile;
private final float hotwordsScore;
public OnlineRecognizerConfig(
FeatureConfig featConfig,
OnlineModelConfig modelConfig,
EndpointConfig endpointConfig,
OnlineLMConfig lmConfig,
boolean enableEndpoint,
String decodingMethod,
int maxActivePaths,
String hotwordsFile,
float hotwordsScore) {
this.featConfig = featConfig;
this.modelConfig = modelConfig;
this.endpointConfig = endpointConfig;
this.lmConfig = lmConfig;
this.enableEndpoint = enableEndpoint;
this.decodingMethod = decodingMethod;
this.maxActivePaths = maxActivePaths;
this.hotwordsFile = hotwordsFile;
this.hotwordsScore = hotwordsScore;
private OnlineRecognizerConfig(Builder builder) {
this.featConfig = builder.featConfig;
this.modelConfig = builder.modelConfig;
this.lmConfig = builder.lmConfig;
this.endpointConfig = builder.endpointConfig;
this.enableEndpoint = builder.enableEndpoint;
this.decodingMethod = builder.decodingMethod;
this.maxActivePaths = builder.maxActivePaths;
this.hotwordsFile = builder.hotwordsFile;
this.hotwordsScore = builder.hotwordsScore;
}
public OnlineLMConfig getLmConfig() {
return lmConfig;
}
public FeatureConfig getFeatConfig() {
return featConfig;
public static Builder builder() {
return new Builder();
}
public OnlineModelConfig getModelConfig() {
return modelConfig;
}
public EndpointConfig getEndpointConfig() {
return endpointConfig;
}
public static class Builder {
private FeatureConfig featConfig = FeatureConfig.builder().build();
private OnlineModelConfig modelConfig = OnlineModelConfig.builder().build();
private OnlineLMConfig lmConfig = OnlineLMConfig.builder().build();
private EndpointConfig endpointConfig = EndpointConfig.builder().build();
private boolean enableEndpoint = true;
private String decodingMethod = "greedy_search";
private int maxActivePaths = 4;
private String hotwordsFile = "";
private float hotwordsScore = 1.5f;
public boolean isEnableEndpoint() {
return enableEndpoint;
}
public OnlineRecognizerConfig build() {
return new OnlineRecognizerConfig(this);
}
public String getDecodingMethod() {
return decodingMethod;
}
public Builder setFeatureConfig(FeatureConfig featConfig) {
this.featConfig = featConfig;
return this;
}
public Builder setOnlineModelConfig(OnlineModelConfig modelConfig) {
this.modelConfig = modelConfig;
return this;
}
public Builder setOnlineLMConfig(OnlineLMConfig lmConfig) {
this.lmConfig = lmConfig;
return this;
}
public Builder setEndpointConfig(EndpointConfig endpointConfig) {
this.endpointConfig = endpointConfig;
return this;
}
public Builder setEnableEndpoint(boolean enableEndpoint) {
this.enableEndpoint = enableEndpoint;
return this;
}
public Builder setDecodingMethod(String decodingMethod) {
this.decodingMethod = decodingMethod;
return this;
}
public Builder setMaxActivePaths(int maxActivePaths) {
this.maxActivePaths = maxActivePaths;
return this;
}
public Builder setHotwordsFile(String hotwordsFile) {
this.hotwordsFile = hotwordsFile;
return this;
}
public int getMaxActivePaths() {
return maxActivePaths;
public Builder setHotwordsScore(float hotwordsScore) {
this.hotwordsScore = hotwordsScore;
return this;
}
}
}
... ...
// Copyright 2024 Xiaomi Corporation
package com.k2fsa.sherpa.onnx;
public class OnlineRecognizerResult {
private final String text;
private final String[] tokens;
private final float[] timestamps;
public OnlineRecognizerResult(String text, String[] tokens, float[] timestamps) {
this.text = text;
this.tokens = tokens;
this.timestamps = timestamps;
}
public String getText() {
return text;
}
public String[] getTokens() {
return tokens;
}
public float[] getTimestamps() {
return timestamps;
}
}
... ...
/*
* // Copyright 2022-2023 by zhaoming
*/
// Stream is used for feeding data to the asr engine
// Copyright 2022-2023 by zhaoming
// Copyright 2024 Xiaomi Corporation
package com.k2fsa.sherpa.onnx;
public class OnlineStream {
private long ptr = 0; // this is the stream ptr
static {
System.loadLibrary("sherpa-onnx-jni");
}
private int sampleRate = 16000;
private long ptr = 0;
// assign ptr to this stream in construction
public OnlineStream(long ptr, int sampleRate) {
this.ptr = ptr;
this.sampleRate = sampleRate;
public OnlineStream() {
this.ptr = 0;
}
public static void loadSoLib(String soPath) {
// load .so lib from the path
System.load(soPath.trim()); // ("sherpa-onnx-jni-java");
public OnlineStream(long ptr) {
this.ptr = ptr;
}
public long getPtr() {
return ptr;
}
public void acceptWaveform(float[] samples) throws Exception {
if (this.ptr == 0) throw new Exception("null exception for stream ptr");
public void setPtr(long ptr) {
this.ptr = ptr;
}
// feed wave data to asr engine
acceptWaveform(this.ptr, this.sampleRate, samples);
public void acceptWaveform(float[] samples, int sampleRate) {
acceptWaveform(this.ptr, samples, sampleRate);
}
public void inputFinished() {
// add some tail padding
int padLen = (int) (this.sampleRate * 0.3); // 0.3 seconds at 16 kHz sample rate
float[] tailPaddings = new float[padLen]; // default value is 0
acceptWaveform(this.ptr, this.sampleRate, tailPaddings);
// tell the engine all data are feeded
inputFinished(this.ptr);
}
public void release() {
// stream object must be release after used
if (this.ptr == 0) return;
deleteStream(this.ptr);
if (this.ptr == 0) {
return;
}
delete(this.ptr);
this.ptr = 0;
}
@Override
protected void finalize() throws Throwable {
release();
super.finalize();
}
public boolean isLastFrame() throws Exception {
if (this.ptr == 0) throw new Exception("null exception for stream ptr");
return isLastFrame(this.ptr);
}
public void reSet() throws Exception {
if (this.ptr == 0) throw new Exception("null exception for stream ptr");
reSet(this.ptr);
}
public int featureDim() throws Exception {
if (this.ptr == 0) throw new Exception("null exception for stream ptr");
return featureDim(this.ptr);
}
// JNI interface libsherpa-onnx-jni.so
private native void acceptWaveform(long ptr, int sampleRate, float[] samples);
private native void acceptWaveform(long ptr, float[] samples, int sampleRate);
private native void inputFinished(long ptr);
private native void deleteStream(long ptr);
private native int numFramesReady(long ptr);
private native boolean isLastFrame(long ptr);
private native void reSet(long ptr);
private native int featureDim(long ptr);
}
private native void delete(long ptr);
}
\ No newline at end of file
... ...
/*
* // Copyright 2022-2023 by zhaoming
*/
// Copyright 2022-2023 by zhaoming
// Copyright 2024 Xiaomi Corporation
package com.k2fsa.sherpa.onnx;
... ... @@ -9,10 +8,14 @@ public class OnlineTransducerModelConfig {
private final String decoder;
private final String joiner;
public OnlineTransducerModelConfig(String encoder, String decoder, String joiner) {
this.encoder = encoder;
this.decoder = decoder;
this.joiner = joiner;
private OnlineTransducerModelConfig(Builder builder) {
this.encoder = builder.encoder;
this.decoder = builder.decoder;
this.joiner = builder.joiner;
}
public static Builder builder() {
return new Builder();
}
public String getEncoder() {
... ... @@ -26,4 +29,29 @@ public class OnlineTransducerModelConfig {
public String getJoiner() {
return joiner;
}
public static class Builder {
private String encoder = "";
private String decoder = "";
private String joiner = "";
public OnlineTransducerModelConfig build() {
return new OnlineTransducerModelConfig(this);
}
public Builder setEncoder(String encoder) {
this.encoder = encoder;
return this;
}
public Builder setDecoder(String decoder) {
this.decoder = decoder;
return this;
}
public Builder setJoiner(String joiner) {
this.joiner = joiner;
return this;
}
}
}
... ...
// Copyright 2024 Xiaomi Corporation
package com.k2fsa.sherpa.onnx;
public class OnlineZipformer2CtcModelConfig {
private final String model;
public OnlineZipformer2CtcModelConfig(String model) {
this.model = model;
private OnlineZipformer2CtcModelConfig(Builder builder) {
this.model = builder.model;
}
public static Builder builder() {
return new Builder();
}
public String getModel() {
return model;
}
public static class Builder {
private String model = "";
public OnlineZipformer2CtcModelConfig build() {
return new OnlineZipformer2CtcModelConfig(this);
}
public Builder setModel(String model) {
this.model = model;
return this;
}
}
}
... ...
// Copyright 2024 Xiaomi Corporation
package com.k2fsa.sherpa.onnx;
public class WaveReader {
static {
System.loadLibrary("sherpa-onnx-jni");
}
private final int sampleRate;
private final float[] samples;
// It supports only single channel, 16-bit wave file.
// It will exit the program if the given file has a wrong format
public WaveReader(String filename) {
Object[] arr = readWaveFromFile(filename);
samples = (float[]) arr[0];
sampleRate = (int) arr[1];
}
public int getSampleRate() {
return sampleRate;
}
public float[] getSamples() {
return samples;
}
private native Object[] readWaveFromFile(String filename);
}
... ...
... ... @@ -21,6 +21,7 @@ set(sources
speaker-embedding-manager.cc
spoken-language-identification.cc
voice-activity-detector.cc
wave-reader.cc
)
if(SHERPA_ONNX_ENABLE_TTS)
... ...
... ... @@ -8,7 +8,6 @@
#include "sherpa-onnx/csrc/macros.h"
#include "sherpa-onnx/csrc/onnx-utils.h"
#include "sherpa-onnx/csrc/wave-reader.h"
#include "sherpa-onnx/csrc/wave-writer.h"
#include "sherpa-onnx/jni/common.h"
... ... @@ -43,69 +42,6 @@ JNIEXPORT jboolean JNICALL Java_com_k2fsa_sherpa_onnx_GeneratedAudio_saveImpl(
return ok;
}
static jobjectArray ReadWaveImpl(JNIEnv *env, std::istream &is,
const char *p_filename) {
bool is_ok = false;
int32_t sampling_rate = -1;
std::vector<float> samples =
sherpa_onnx::ReadWave(is, &sampling_rate, &is_ok);
if (!is_ok) {
SHERPA_ONNX_LOGE("Failed to read %s", p_filename);
exit(-1);
}
jfloatArray samples_arr = env->NewFloatArray(samples.size());
env->SetFloatArrayRegion(samples_arr, 0, samples.size(), samples.data());
jobjectArray obj_arr = (jobjectArray)env->NewObjectArray(
2, env->FindClass("java/lang/Object"), nullptr);
env->SetObjectArrayElement(obj_arr, 0, samples_arr);
env->SetObjectArrayElement(obj_arr, 1, NewInteger(env, sampling_rate));
return obj_arr;
}
SHERPA_ONNX_EXTERN_C
JNIEXPORT jobjectArray JNICALL
Java_com_k2fsa_sherpa_onnx_WaveReader_00024Companion_readWaveFromFile(
JNIEnv *env, jclass /*cls*/, jstring filename) {
const char *p_filename = env->GetStringUTFChars(filename, nullptr);
std::ifstream is(p_filename, std::ios::binary);
auto obj_arr = ReadWaveImpl(env, is, p_filename);
env->ReleaseStringUTFChars(filename, p_filename);
return obj_arr;
}
SHERPA_ONNX_EXTERN_C
JNIEXPORT jobjectArray JNICALL
Java_com_k2fsa_sherpa_onnx_WaveReader_00024Companion_readWaveFromAsset(
JNIEnv *env, jclass /*cls*/, jobject asset_manager, jstring filename) {
const char *p_filename = env->GetStringUTFChars(filename, nullptr);
#if __ANDROID_API__ >= 9
AAssetManager *mgr = AAssetManager_fromJava(env, asset_manager);
if (!mgr) {
SHERPA_ONNX_LOGE("Failed to get asset manager: %p", mgr);
exit(-1);
}
std::vector<char> buffer = sherpa_onnx::ReadFile(mgr, p_filename);
std::istrstream is(buffer.data(), buffer.size());
#else
std::ifstream is(p_filename, std::ios::binary);
#endif
auto obj_arr = ReadWaveImpl(env, is, p_filename);
env->ReleaseStringUTFChars(filename, p_filename);
return obj_arr;
}
#if 0
SHERPA_ONNX_EXTERN_C
JNIEXPORT void JNICALL
... ...
// sherpa-onnx/jni/wave-reader.cc
//
// Copyright (c) 2024 Xiaomi Corporation
#include "sherpa-onnx/csrc/wave-reader.h"
#include <fstream>
#include "sherpa-onnx/csrc/macros.h"
#include "sherpa-onnx/jni/common.h"
static jobjectArray ReadWaveImpl(JNIEnv *env, std::istream &is,
const char *p_filename) {
bool is_ok = false;
int32_t sampling_rate = -1;
std::vector<float> samples =
sherpa_onnx::ReadWave(is, &sampling_rate, &is_ok);
if (!is_ok) {
SHERPA_ONNX_LOGE("Failed to read '%s'", p_filename);
exit(-1);
}
jfloatArray samples_arr = env->NewFloatArray(samples.size());
env->SetFloatArrayRegion(samples_arr, 0, samples.size(), samples.data());
jobjectArray obj_arr = (jobjectArray)env->NewObjectArray(
2, env->FindClass("java/lang/Object"), nullptr);
env->SetObjectArrayElement(obj_arr, 0, samples_arr);
env->SetObjectArrayElement(obj_arr, 1, NewInteger(env, sampling_rate));
return obj_arr;
}
SHERPA_ONNX_EXTERN_C
JNIEXPORT jobjectArray JNICALL
Java_com_k2fsa_sherpa_onnx_WaveReader_00024Companion_readWaveFromFile(
JNIEnv *env, jclass /*cls*/, jstring filename) {
const char *p_filename = env->GetStringUTFChars(filename, nullptr);
std::ifstream is(p_filename, std::ios::binary);
auto obj_arr = ReadWaveImpl(env, is, p_filename);
env->ReleaseStringUTFChars(filename, p_filename);
return obj_arr;
}
SHERPA_ONNX_EXTERN_C
JNIEXPORT jobjectArray JNICALL
Java_com_k2fsa_sherpa_onnx_WaveReader_readWaveFromFile(JNIEnv *env,
jclass /*obj*/,
jstring filename) {
return Java_com_k2fsa_sherpa_onnx_WaveReader_00024Companion_readWaveFromFile(
env, nullptr, filename);
}
SHERPA_ONNX_EXTERN_C
JNIEXPORT jobjectArray JNICALL
Java_com_k2fsa_sherpa_onnx_WaveReader_00024Companion_readWaveFromAsset(
JNIEnv *env, jclass /*cls*/, jobject asset_manager, jstring filename) {
const char *p_filename = env->GetStringUTFChars(filename, nullptr);
#if __ANDROID_API__ >= 9
AAssetManager *mgr = AAssetManager_fromJava(env, asset_manager);
if (!mgr) {
SHERPA_ONNX_LOGE("Failed to get asset manager: %p", mgr);
exit(-1);
}
std::vector<char> buffer = sherpa_onnx::ReadFile(mgr, p_filename);
std::istrstream is(buffer.data(), buffer.size());
#else
std::ifstream is(p_filename, std::ios::binary);
#endif
auto obj_arr = ReadWaveImpl(env, is, p_filename);
env->ReleaseStringUTFChars(filename, p_filename);
return obj_arr;
}
... ...