xuning / sherpaonnx

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Fangjun Kuang
Committed by GitHub
a8bdb4b3 1 parent 35526e26

Support paraformer on iOS (#265) 

* Fix C API to support streaming paraformer

* Fix Swift API

* Support paraformer in iOS
内嵌 并排对比
正在显示 12 个修改的文件 包含 203 行增加 和 85 行删除
... ... @@ -113,13 +113,13 @@ int32_t main(int32_t argc, char *argv[]) {
config.model_config.tokens = value;
break;
case 'e':
config.model_config.encoder = value;
config.model_config.transducer.encoder = value;
break;
case 'd':
config.model_config.decoder = value;
config.model_config.transducer.decoder = value;
break;
case 'j':
config.model_config.joiner = value;
config.model_config.transducer.joiner = value;
break;
case 'n':
config.model_config.num_threads = atoi(value);
... ...
... ... @@ -7,6 +7,8 @@
objects = {
/* Begin PBXBuildFile section */
C93989AE2A89FE13009AB859 /* sherpa-onnx.xcframework in Frameworks */ = {isa = PBXBuildFile; fileRef = C984A81B29AA11C500D74C52 /* sherpa-onnx.xcframework */; };
C93989B02A89FE33009AB859 /* onnxruntime.xcframework in Frameworks */ = {isa = PBXBuildFile; fileRef = C93989AF2A89FE33009AB859 /* onnxruntime.xcframework */; };
C984A7E829A9EEB700D74C52 /* AppDelegate.swift in Sources */ = {isa = PBXBuildFile; fileRef = C984A7E729A9EEB700D74C52 /* AppDelegate.swift */; };
C984A7EA29A9EEB700D74C52 /* SceneDelegate.swift in Sources */ = {isa = PBXBuildFile; fileRef = C984A7E929A9EEB700D74C52 /* SceneDelegate.swift */; };
C984A7F129A9EEB900D74C52 /* Assets.xcassets in Resources */ = {isa = PBXBuildFile; fileRef = C984A7F029A9EEB900D74C52 /* Assets.xcassets */; };
... ... @@ -18,8 +20,6 @@
C984A82829AA196100D74C52 /* Main.storyboard in Resources */ = {isa = PBXBuildFile; fileRef = C984A82629AA196100D74C52 /* Main.storyboard */; };
C984A82A29AA19AC00D74C52 /* Model.swift in Sources */ = {isa = PBXBuildFile; fileRef = C984A82929AA19AC00D74C52 /* Model.swift */; };
C984A83C29AA430B00D74C52 /* ViewController.swift in Sources */ = {isa = PBXBuildFile; fileRef = C984A83B29AA430B00D74C52 /* ViewController.swift */; };
C984A83D29AA43D900D74C52 /* sherpa-onnx.xcframework in Frameworks */ = {isa = PBXBuildFile; fileRef = C984A81B29AA11C500D74C52 /* sherpa-onnx.xcframework */; };
C984A83F29AA43EE00D74C52 /* onnxruntime.xcframework in Frameworks */ = {isa = PBXBuildFile; fileRef = C984A83E29AA43EE00D74C52 /* onnxruntime.xcframework */; };
/* End PBXBuildFile section */
/* Begin PBXContainerItemProxy section */
... ... @@ -40,6 +40,10 @@
/* End PBXContainerItemProxy section */
/* Begin PBXFileReference section */
C93989AF2A89FE33009AB859 /* onnxruntime.xcframework */ = {isa = PBXFileReference; lastKnownFileType = wrapper.xcframework; name = onnxruntime.xcframework; path = "../../build-ios/ios-onnxruntime/1.15.1/onnxruntime.xcframework"; sourceTree = "<group>"; };
C93989B12A89FF78009AB859 /* decoder.int8.onnx */ = {isa = PBXFileReference; lastKnownFileType = file; name = decoder.int8.onnx; path = "../../../icefall-models/sherpa-onnx-streaming-paraformer-bilingual-zh-en/decoder.int8.onnx"; sourceTree = "<group>"; };
C93989B22A89FF78009AB859 /* encoder.int8.onnx */ = {isa = PBXFileReference; lastKnownFileType = file; name = encoder.int8.onnx; path = "../../../icefall-models/sherpa-onnx-streaming-paraformer-bilingual-zh-en/encoder.int8.onnx"; sourceTree = "<group>"; };
C93989B32A89FF78009AB859 /* tokens.txt */ = {isa = PBXFileReference; lastKnownFileType = text; name = tokens.txt; path = "../../../icefall-models/sherpa-onnx-streaming-paraformer-bilingual-zh-en/tokens.txt"; sourceTree = "<group>"; };
C984A7E429A9EEB700D74C52 /* SherpaOnnx.app */ = {isa = PBXFileReference; explicitFileType = wrapper.application; includeInIndex = 0; path = SherpaOnnx.app; sourceTree = BUILT_PRODUCTS_DIR; };
C984A7E729A9EEB700D74C52 /* AppDelegate.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = AppDelegate.swift; sourceTree = "<group>"; };
C984A7E929A9EEB700D74C52 /* SceneDelegate.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = SceneDelegate.swift; sourceTree = "<group>"; };
... ... @@ -66,8 +70,8 @@
isa = PBXFrameworksBuildPhase;
buildActionMask = 2147483647;
files = (
C984A83F29AA43EE00D74C52 /* onnxruntime.xcframework in Frameworks */,
C984A83D29AA43D900D74C52 /* sherpa-onnx.xcframework in Frameworks */,
C93989B02A89FE33009AB859 /* onnxruntime.xcframework in Frameworks */,
C93989AE2A89FE13009AB859 /* sherpa-onnx.xcframework in Frameworks */,
);
runOnlyForDeploymentPostprocessing = 0;
};
... ... @@ -146,8 +150,12 @@
C984A81A29AA11C500D74C52 /* Frameworks */ = {
isa = PBXGroup;
children = (
C93989B12A89FF78009AB859 /* decoder.int8.onnx */,
C93989B22A89FF78009AB859 /* encoder.int8.onnx */,
C93989B32A89FF78009AB859 /* tokens.txt */,
C984A82029AA139600D74C52 /* onnxruntime.xcframework */,
C984A83E29AA43EE00D74C52 /* onnxruntime.xcframework */,
C93989AF2A89FE33009AB859 /* onnxruntime.xcframework */,
C984A81B29AA11C500D74C52 /* sherpa-onnx.xcframework */,
);
name = Frameworks;
... ...
... ... @@ -15,70 +15,91 @@ func getResource(_ forResource: String, _ ofType: String) -> String {
/// sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20 (Bilingual, Chinese + English)
/// https://k2-fsa.github.io/sherpa/onnx/pretrained_models/zipformer-transducer-models.html
func getBilingualStreamZhEnZipformer20230220() -> SherpaOnnxOnlineTransducerModelConfig {
func getBilingualStreamZhEnZipformer20230220() -> SherpaOnnxOnlineModelConfig {
let encoder = getResource("encoder-epoch-99-avg-1", "onnx")
let decoder = getResource("decoder-epoch-99-avg-1", "onnx")
let joiner = getResource("joiner-epoch-99-avg-1", "onnx")
let tokens = getResource("tokens", "txt")
return sherpaOnnxOnlineTransducerModelConfig(
encoder: encoder,
decoder: decoder,
joiner: joiner,
return sherpaOnnxOnlineModelConfig(
tokens: tokens,
numThreads: 2,
transducer: sherpaOnnxOnlineTransducerModelConfig(
encoder: encoder,
decoder: decoder,
joiner: joiner
),
numThreads: 1,
modelType: "zipformer"
)
}
func getZhZipformer20230615() -> SherpaOnnxOnlineTransducerModelConfig {
func getZhZipformer20230615() -> SherpaOnnxOnlineModelConfig {
let encoder = getResource("encoder-epoch-12-avg-4-chunk-16-left-128", "onnx")
let decoder = getResource("decoder-epoch-12-avg-4-chunk-16-left-128", "onnx")
let joiner = getResource("joiner-epoch-12-avg-4-chunk-16-left-128", "onnx")
let tokens = getResource("tokens", "txt")
return sherpaOnnxOnlineTransducerModelConfig(
encoder: encoder,
decoder: decoder,
joiner: joiner,
return sherpaOnnxOnlineModelConfig(
tokens: tokens,
numThreads: 2,
transducer: sherpaOnnxOnlineTransducerModelConfig(
encoder: encoder,
decoder: decoder,
joiner: joiner
),
numThreads: 1,
modelType: "zipformer2"
)
}
func getZhZipformer20230615Int8() -> SherpaOnnxOnlineTransducerModelConfig {
func getZhZipformer20230615Int8() -> SherpaOnnxOnlineModelConfig {
let encoder = getResource("encoder-epoch-12-avg-4-chunk-16-left-128.int8", "onnx")
let decoder = getResource("decoder-epoch-12-avg-4-chunk-16-left-128", "onnx")
let joiner = getResource("joiner-epoch-12-avg-4-chunk-16-left-128", "onnx")
let tokens = getResource("tokens", "txt")
return sherpaOnnxOnlineTransducerModelConfig(
encoder: encoder,
decoder: decoder,
joiner: joiner,
return sherpaOnnxOnlineModelConfig(
tokens: tokens,
numThreads: 2,
transducer: sherpaOnnxOnlineTransducerModelConfig(
encoder: encoder,
decoder: decoder,
joiner: joiner),
numThreads: 1,
modelType: "zipformer2"
)
}
func getEnZipformer20230626() -> SherpaOnnxOnlineTransducerModelConfig {
func getEnZipformer20230626() -> SherpaOnnxOnlineModelConfig {
let encoder = getResource("encoder-epoch-99-avg-1-chunk-16-left-128", "onnx")
let decoder = getResource("decoder-epoch-99-avg-1-chunk-16-left-128", "onnx")
let joiner = getResource("joiner-epoch-99-avg-1-chunk-16-left-128", "onnx")
let tokens = getResource("tokens", "txt")
return sherpaOnnxOnlineTransducerModelConfig(
encoder: encoder,
decoder: decoder,
joiner: joiner,
return sherpaOnnxOnlineModelConfig(
tokens: tokens,
numThreads: 2,
transducer: sherpaOnnxOnlineTransducerModelConfig(
encoder: encoder,
decoder: decoder,
joiner: joiner),
numThreads: 1,
modelType: "zipformer2"
)
}
func getBilingualStreamingZhEnParaformer() -> SherpaOnnxOnlineModelConfig {
let encoder = getResource("encoder.int8", "onnx")
let decoder = getResource("decoder.int8", "onnx")
let tokens = getResource("tokens", "txt")
return sherpaOnnxOnlineModelConfig(
tokens: tokens,
paraformer: sherpaOnnxOnlineParaformerModelConfig(
encoder: encoder,
decoder: decoder),
numThreads: 1,
modelType: "paraformer"
)
}
/// Please refer to
/// https://k2-fsa.github.io/sherpa/onnx/pretrained_models/index.html
/// to add more models if you need
... ...
... ... @@ -87,7 +87,8 @@ class ViewController: UIViewController {
// let modelConfig = getBilingualStreamZhEnZipformer20230220()
// let modelConfig = getZhZipformer20230615()
let modelConfig = getEnZipformer20230626()
// let modelConfig = getEnZipformer20230626()
let modelConfig = getBilingualStreamingZhEnParaformer()
let featConfig = sherpaOnnxFeatureConfig(
sampleRate: 16000,
... ...
... ... @@ -15,22 +15,39 @@ func getResource(_ forResource: String, _ ofType: String) -> String {
/// sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20 (Bilingual, Chinese + English)
/// https://k2-fsa.github.io/sherpa/onnx/pretrained_models/zipformer-transducer-models.html
func getBilingualStreamZhEnZipformer20230220() -> SherpaOnnxOnlineTransducerModelConfig {
func getBilingualStreamZhEnZipformer20230220() -> SherpaOnnxOnlineModelConfig {
let encoder = getResource("encoder-epoch-99-avg-1", "onnx")
let decoder = getResource("decoder-epoch-99-avg-1", "onnx")
let joiner = getResource("joiner-epoch-99-avg-1", "onnx")
let tokens = getResource("tokens", "txt")
return sherpaOnnxOnlineTransducerModelConfig(
encoder: encoder,
decoder: decoder,
joiner: joiner,
return sherpaOnnxOnlineModelConfig(
tokens: tokens,
transducer: sherpaOnnxOnlineTransducerModelConfig(
encoder: encoder,
decoder: decoder,
joiner: joiner),
numThreads: 2,
modelType: "zipformer"
)
}
// https://k2-fsa.github.io/sherpa/onnx/pretrained_models/online-paraformer/index.html
func getBilingualStreamingZhEnParaformer() -> SherpaOnnxOnlineModelConfig {
let encoder = getResource("encoder.int8", "onnx")
let decoder = getResource("decoder.int8", "onnx")
let tokens = getResource("tokens", "txt")
return sherpaOnnxOnlineModelConfig(
tokens: tokens,
paraformer: sherpaOnnxOnlineParaformerModelConfig(
encoder: encoder,
decoder: decoder),
numThreads: 1,
modelType: "paraformer"
)
}
/// Please refer to
/// https://k2-fsa.github.io/sherpa/onnx/pretrained_models/index.html
/// to add more models if you need
... ...
... ... @@ -16,15 +16,15 @@ enum Status {
class SherpaOnnxViewModel: ObservableObject {
@Published var status: Status = .stop
@Published var subtitles: String = ""
var sentences: [String] = []
var audioEngine: AVAudioEngine? = nil
var recognizer: SherpaOnnxRecognizer! = nil
var lastSentence: String = ""
let maxSentence: Int = 20
var results: String {
if sentences.isEmpty && lastSentence.isEmpty {
return ""
... ... @@ -42,24 +42,25 @@ class SherpaOnnxViewModel: ObservableObject {
.joined(separator: "\n") + "\n\(sentences.count): \(lastSentence.lowercased())"
}
}
func updateLabel() {
DispatchQueue.main.async {
self.subtitles = self.results
}
}
init() {
initRecognizer()
initRecorder()
}
private func initRecognizer() {
// Please select one model that is best suitable for you.
//
// You can also modify Model.swift to add new pre-trained models from
// https://k2-fsa.github.io/sherpa/onnx/pretrained_models/index.html
let modelConfig = getBilingualStreamZhEnZipformer20230220()
// let modelConfig = getBilingualStreamZhEnZipformer20230220()
let modelConfig = getBilingualStreamingZhEnParaformer()
let featConfig = sherpaOnnxFeatureConfig(
sampleRate: 16000,
... ... @@ -77,7 +78,7 @@ class SherpaOnnxViewModel: ObservableObject {
)
recognizer = SherpaOnnxRecognizer(config: &config)
}
private func initRecorder() {
print("init recorder")
audioEngine = AVAudioEngine()
... ... @@ -152,7 +153,7 @@ class SherpaOnnxViewModel: ObservableObject {
}
}
}
public func toggleRecorder() {
if status == .stop {
startRecorder()
... ...
... ... @@ -39,11 +39,17 @@ SherpaOnnxOnlineRecognizer *CreateOnlineRecognizer(
SHERPA_ONNX_OR(config->feat_config.feature_dim, 80);
recognizer_config.model_config.transducer.encoder =
SHERPA_ONNX_OR(config->model_config.encoder, "");
SHERPA_ONNX_OR(config->model_config.transducer.encoder, "");
recognizer_config.model_config.transducer.decoder =
SHERPA_ONNX_OR(config->model_config.decoder, "");
SHERPA_ONNX_OR(config->model_config.transducer.decoder, "");
recognizer_config.model_config.transducer.joiner =
SHERPA_ONNX_OR(config->model_config.joiner, "");
SHERPA_ONNX_OR(config->model_config.transducer.joiner, "");
recognizer_config.model_config.paraformer.encoder =
SHERPA_ONNX_OR(config->model_config.paraformer.encoder, "");
recognizer_config.model_config.paraformer.decoder =
SHERPA_ONNX_OR(config->model_config.paraformer.decoder, "");
recognizer_config.model_config.tokens =
SHERPA_ONNX_OR(config->model_config.tokens, "");
recognizer_config.model_config.num_threads =
... ... @@ -128,6 +134,8 @@ SherpaOnnxOnlineRecognizerResult *GetOnlineStreamResult(
const auto &text = result.text;
auto r = new SherpaOnnxOnlineRecognizerResult;
memset(r, 0, sizeof(SherpaOnnxOnlineRecognizerResult));
// copy text
r->text = new char[text.size() + 1];
std::copy(text.begin(), text.end(), const_cast<char *>(r->text));
... ... @@ -153,7 +161,6 @@ SherpaOnnxOnlineRecognizerResult *GetOnlineStreamResult(
r->tokens = new char[total_length];
memset(reinterpret_cast<void *>(const_cast<char *>(r->tokens)), 0,
total_length);
r->timestamps = new float[r->count];
char **tokens_temp = new char *[r->count];
int32_t pos = 0;
for (int32_t i = 0; i < r->count; ++i) {
... ... @@ -162,10 +169,17 @@ SherpaOnnxOnlineRecognizerResult *GetOnlineStreamResult(
result.tokens[i].c_str(), result.tokens[i].size());
// +1 to move past the null character
pos += result.tokens[i].size() + 1;
r->timestamps[i] = result.timestamps[i];
}
r->tokens_arr = tokens_temp;
if (!result.timestamps.empty()) {
r->timestamps = new float[r->count];
std::copy(result.timestamps.begin(), result.timestamps.end(),
r->timestamps);
} else {
r->timestamps = nullptr;
}
} else {
r->count = 0;
r->timestamps = nullptr;
... ...
... ... @@ -50,12 +50,25 @@ SHERPA_ONNX_API typedef struct SherpaOnnxOnlineTransducerModelConfig {
const char *encoder;
const char *decoder;
const char *joiner;
} SherpaOnnxOnlineTransducerModelConfig;
// please visit
// https://k2-fsa.github.io/sherpa/onnx/pretrained_models/online-paraformer/index.html
// to download pre-trained streaming paraformer models
SHERPA_ONNX_API typedef struct SherpaOnnxOnlineParaformerModelConfig {
const char *encoder;
const char *decoder;
} SherpaOnnxOnlineParaformerModelConfig;
SHERPA_ONNX_API typedef struct SherpaOnnxModelConfig {
SherpaOnnxOnlineTransducerModelConfig transducer;
SherpaOnnxOnlineParaformerModelConfig paraformer;
const char *tokens;
int32_t num_threads;
const char *provider;
int32_t debug; // true to print debug information of the model
const char *model_type;
} SherpaOnnxOnlineTransducerModelConfig;
} SherpaOnnxOnlineModelConfig;
/// It expects 16 kHz 16-bit single channel wave format.
SHERPA_ONNX_API typedef struct SherpaOnnxFeatureConfig {
... ... @@ -71,7 +84,7 @@ SHERPA_ONNX_API typedef struct SherpaOnnxFeatureConfig {
SHERPA_ONNX_API typedef struct SherpaOnnxOnlineRecognizerConfig {
SherpaOnnxFeatureConfig feat_config;
SherpaOnnxOnlineTransducerModelConfig model_config;
SherpaOnnxOnlineModelConfig model_config;
/// Possible values are: greedy_search, modified_beam_search
const char *decoding_method;
... ...
... ... @@ -18,31 +18,71 @@ func toCPointer(_ s: String) -> UnsafePointer<Int8>! {
/// Return an instance of SherpaOnnxOnlineTransducerModelConfig.
///
/// Please refer to
/// https://k2-fsa.github.io/sherpa/onnx/pretrained_models/index.html
/// https://k2-fsa.github.io/sherpa/onnx/pretrained_models/online-transducer/index.html
/// to download the required `.onnx` files.
///
/// - Parameters:
/// - encoder: Path to encoder.onnx
/// - decoder: Path to decoder.onnx
/// - joiner: Path to joiner.onnx
///
/// - Returns: Return an instance of SherpaOnnxOnlineTransducerModelConfig
func sherpaOnnxOnlineTransducerModelConfig(
encoder: String = "",
decoder: String = "",
joiner: String = ""
) -> SherpaOnnxOnlineTransducerModelConfig {
return SherpaOnnxOnlineTransducerModelConfig(
encoder: toCPointer(encoder),
decoder: toCPointer(decoder),
joiner: toCPointer(joiner)
)
}
/// Return an instance of SherpaOnnxOnlineParaformerModelConfig.
///
/// Please refer to
/// https://k2-fsa.github.io/sherpa/onnx/pretrained_models/online-paraformer/index.html
/// to download the required `.onnx` files.
///
/// - Parameters:
/// - encoder: Path to encoder.onnx
/// - decoder: Path to decoder.onnx
///
/// - Returns: Return an instance of SherpaOnnxOnlineParaformerModelConfig
func sherpaOnnxOnlineParaformerModelConfig(
encoder: String = "",
decoder: String = ""
) -> SherpaOnnxOnlineParaformerModelConfig {
return SherpaOnnxOnlineParaformerModelConfig(
encoder: toCPointer(encoder),
decoder: toCPointer(decoder)
)
}
/// Return an instance of SherpaOnnxOnlineModelConfig.
///
/// Please refer to
/// https://k2-fsa.github.io/sherpa/onnx/pretrained_models/index.html
/// to download the required `.onnx` files.
///
/// - Parameters:
/// - tokens: Path to tokens.txt
/// - numThreads: Number of threads to use for neural network computation.
///
/// - Returns: Return an instance of SherpaOnnxOnlineTransducerModelConfig
func sherpaOnnxOnlineTransducerModelConfig(
encoder: String,
decoder: String,
joiner: String,
func sherpaOnnxOnlineModelConfig(
tokens: String,
numThreads: Int = 2,
transducer: SherpaOnnxOnlineTransducerModelConfig = sherpaOnnxOnlineTransducerModelConfig(),
paraformer: SherpaOnnxOnlineParaformerModelConfig = sherpaOnnxOnlineParaformerModelConfig(),
numThreads: Int = 1,
provider: String = "cpu",
debug: Int = 0,
modelType: String = ""
) -> SherpaOnnxOnlineTransducerModelConfig {
return SherpaOnnxOnlineTransducerModelConfig(
encoder: toCPointer(encoder),
decoder: toCPointer(decoder),
joiner: toCPointer(joiner),
) -> SherpaOnnxOnlineModelConfig {
return SherpaOnnxOnlineModelConfig(
transducer: transducer,
paraformer: paraformer,
tokens: toCPointer(tokens),
num_threads: Int32(numThreads),
provider: toCPointer(provider),
... ... @@ -62,7 +102,7 @@ func sherpaOnnxFeatureConfig(
func sherpaOnnxOnlineRecognizerConfig(
featConfig: SherpaOnnxFeatureConfig,
modelConfig: SherpaOnnxOnlineTransducerModelConfig,
modelConfig: SherpaOnnxOnlineModelConfig,
enableEndpoint: Bool = false,
rule1MinTrailingSilence: Float = 2.4,
rule2MinTrailingSilence: Float = 1.2,
... ... @@ -100,17 +140,17 @@ class SherpaOnnxOnlineRecongitionResult {
}
var count: Int32 {
return result.pointee.count
return result.pointee.count
}
var tokens: [String] {
if let tokensPointer = result.pointee.tokens_arr {
var tokens: [String] = []
for index in 0..<count {
if let tokenPointer = tokensPointer[Int(index)] {
let token = String(cString: tokenPointer)
tokens.append(token)
}
if let tokenPointer = tokensPointer[Int(index)] {
let token = String(cString: tokenPointer)
tokens.append(token)
}
}
return tokens
} else {
... ...
... ... @@ -13,31 +13,34 @@ extension AVAudioPCMBuffer {
}
func run() {
let encoder = "./sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20/encoder-epoch-99-avg-1.onnx"
let decoder = "./sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20/decoder-epoch-99-avg-1.onnx"
let joiner = "./sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20/joiner-epoch-99-avg-1.onnx"
let encoder =
"./sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20/encoder-epoch-99-avg-1.onnx"
let decoder =
"./sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20/decoder-epoch-99-avg-1.onnx"
let joiner =
"./sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20/joiner-epoch-99-avg-1.onnx"
let tokens = "./sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20/tokens.txt"
let modelConfig = sherpaOnnxOnlineTransducerModelConfig(
let transducerConfig = sherpaOnnxOnlineTransducerModelConfig(
encoder: encoder,
decoder: decoder,
joiner: joiner,
joiner: joiner
)
let modelConfig = sherpaOnnxOnlineModelConfig(
tokens: tokens,
numThreads: 2)
transducer: transducerConfig
)
let featConfig = sherpaOnnxFeatureConfig(
sampleRate: 16000,
featureDim: 80
)
var config = sherpaOnnxOnlineRecognizerConfig(
featConfig: featConfig,
modelConfig: modelConfig,
enableEndpoint: false,
decodingMethod: "modified_beam_search",
maxActivePaths: 4
featConfig: featConfig,
modelConfig: modelConfig
)
let recognizer = SherpaOnnxRecognizer(config: &config)
let filePath = "./sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20/test_wavs/1.wav"
... ... @@ -60,7 +63,7 @@ func run() {
recognizer.acceptWaveform(samples: tailPadding)
recognizer.inputFinished()
while (recognizer.isReady()) {
while recognizer.isReady() {
recognizer.decode()
}
... ...