Add tdt duration to APIs (#2514)

@@ -59,6 +59,9 @@ target_link_libraries(fire-red-asr-c-api sherpa-onnx-c-api)
 add_executable(nemo-canary-c-api nemo-canary-c-api.c)
 target_link_libraries(nemo-canary-c-api sherpa-onnx-c-api)
 
+add_executable(nemo-parakeet-c-api nemo-parakeet-c-api.c)
+target_link_libraries(nemo-parakeet-c-api sherpa-onnx-c-api)
+
 add_executable(sense-voice-c-api sense-voice-c-api.c)
 target_link_libraries(sense-voice-c-api sherpa-onnx-c-api)
 

+// c-api-examples/nemo-parakeet-c-api.c
+// Example using the C API and sherpa-onnx-nemo-parakeet-tdt-0.6b-v3-int8 model
+// Prints recognized text, per-token timestamps, and durations
+
+#include <stdio.h>
+#include <stdlib.h>
+#include <string.h>
+
+#include "sherpa-onnx/c-api/c-api.h"
+
+int32_t main() {
+  const char *wav_filename =
+      "./sherpa-onnx-nemo-parakeet-tdt-0.6b-v3-int8/test_wavs/en.wav";
+  const char *encoder_filename =
+      "sherpa-onnx-nemo-parakeet-tdt-0.6b-v3-int8/encoder.int8.onnx";
+  const char *decoder_filename =
+      "sherpa-onnx-nemo-parakeet-tdt-0.6b-v3-int8/decoder.int8.onnx";
+  const char *joiner_filename =
+      "sherpa-onnx-nemo-parakeet-tdt-0.6b-v3-int8/joiner.int8.onnx";
+  const char *tokens_filename =
+      "sherpa-onnx-nemo-parakeet-tdt-0.6b-v3-int8/tokens.txt";
+  const char *provider = "cpu";
+
+  if (!SherpaOnnxFileExists(wav_filename)) {
+    fprintf(stderr, "File not found: %s\n", wav_filename);
+    return -1;
+  }
+  const SherpaOnnxWave *wave = SherpaOnnxReadWave(wav_filename);
+  if (wave == NULL) {
+    fprintf(stderr, "Failed to read or parse %s (not a valid mono 16-bit WAVE file)\n", wav_filename);
+    return -1;
+  }
+
+  SherpaOnnxOfflineModelConfig offline_model_config;
+  memset(&offline_model_config, 0, sizeof(offline_model_config));
+  offline_model_config.debug = 0;
+  offline_model_config.num_threads = 1;
+  offline_model_config.provider = provider;
+  offline_model_config.tokens = tokens_filename;
+  offline_model_config.transducer.encoder = encoder_filename;
+  offline_model_config.transducer.decoder = decoder_filename;
+  offline_model_config.transducer.joiner = joiner_filename;
+
+  SherpaOnnxOfflineRecognizerConfig recognizer_config;
+  memset(&recognizer_config, 0, sizeof(recognizer_config));
+  recognizer_config.decoding_method = "greedy_search";
+  recognizer_config.model_config = offline_model_config;
+
+  const SherpaOnnxOfflineRecognizer *recognizer =
+      SherpaOnnxCreateOfflineRecognizer(&recognizer_config);
+  if (recognizer == NULL) {
+    fprintf(stderr, "Please check your config!\n");
+    SherpaOnnxFreeWave(wave);
+    return -1;
+  }
+
+  const SherpaOnnxOfflineStream *stream =
+      SherpaOnnxCreateOfflineStream(recognizer);
+  if (stream == NULL) {
+    fprintf(stderr, "Failed to create offline stream.\n");
+    SherpaOnnxDestroyOfflineRecognizer(recognizer);
+    SherpaOnnxFreeWave(wave);
+    return -1;
+  }
+
+  SherpaOnnxAcceptWaveformOffline(stream, wave->sample_rate, wave->samples,
+                                  wave->num_samples);
+  SherpaOnnxDecodeOfflineStream(recognizer, stream);
+  const SherpaOnnxOfflineRecognizerResult *result =
+      SherpaOnnxGetOfflineStreamResult(stream);
+
+  printf("Recognized text: %s\n", result->text);
+
+  if (result->tokens_arr && result->timestamps && result->durations) {
+    printf("Token\tTimestamp\tDuration\n");
+    for (int32_t i = 0; i < result->count; ++i) {
+      printf("%s\t%.2f\t%.2f\n", result->tokens_arr[i], result->timestamps[i], result->durations[i]);
+    }
+  } else {
+    printf("Timestamps or durations not available.\n");
+  }
+
+  SherpaOnnxDestroyOfflineRecognizerResult(result);
+  SherpaOnnxDestroyOfflineStream(stream);
+  SherpaOnnxDestroyOfflineRecognizer(recognizer);
+  SherpaOnnxFreeWave(wave);
+
+  return 0;
+}

+# Example using the sherpa-onnx Python API and sherpa-onnx-nemo-parakeet-tdt-0.6b-v3-int8 model
+# Prints recognized text, per-token timestamps, and durations
+
+import os
+import sys
+import sherpa_onnx
+import soundfile as sf
+
+wav_filename = "./sherpa-onnx-nemo-parakeet-tdt-0.6b-v3-int8/test_wavs/en.wav"
+encoder = "./sherpa-onnx-nemo-parakeet-tdt-0.6b-v3-int8/encoder.int8.onnx"
+decoder = "./sherpa-onnx-nemo-parakeet-tdt-0.6b-v3-int8/decoder.int8.onnx"
+joiner = "./sherpa-onnx-nemo-parakeet-tdt-0.6b-v3-int8/joiner.int8.onnx"
+tokens = "./sherpa-onnx-nemo-parakeet-tdt-0.6b-v3-int8/tokens.txt"
+
+if not os.path.exists(wav_filename):
+    print(f"File not found: {wav_filename}")
+    sys.exit(1)
+
+
+recognizer = sherpa_onnx.OfflineRecognizer.from_transducer(
+    encoder,
+    decoder,
+    joiner,
+    tokens,
+    num_threads=1,
+    provider="cpu",
+    debug=False,
+    decoding_method="greedy_search",
+    model_type="nemo_transducer"
+)
+
+audio, sample_rate = sf.read(wav_filename, dtype="float32", always_2d=True)
+audio = audio[:, 0]  # use first channel if multi-channel
+stream = recognizer.create_stream()
+stream.accept_waveform(sample_rate, audio)
+recognizer.decode_stream(stream)
+result = stream.result
+
+print(f"Recognized text: {result.text}")
+
+if hasattr(result, "tokens") and hasattr(result, "timestamps") and hasattr(result, "durations"):
+    print("Token\tTimestamp\tDuration")
+    for token, ts, dur in zip(result.tokens, result.timestamps, result.durations):
+        print(f"{token}\t{ts:.2f}\t{dur:.2f}")
+else:
+    print("Timestamps or durations not available.")

@@ -523,6 +523,7 @@ type OfflineRecognizerResult struct {
 	Text       string
 	Tokens     []string
 	Timestamps []float32
+	Durations  []float32
 	Lang       string
 	Emotion    string
 	Event      string
@@ -872,13 +873,19 @@ func (s *OfflineStream) GetResult() *OfflineRecognizerResult {
 	for i := 0; i < n; i++ {
 		result.Tokens[i] = C.GoString(tokens[i])
 	}
-	if p.timestamps == nil {
-		return result
+	if p.timestamps != nil {
+		result.Timestamps = make([]float32, n)
+		timestamps := unsafe.Slice(p.timestamps, n)
+		for i := 0; i < n; i++ {
+			result.Timestamps[i] = float32(timestamps[i])
+		}
 	}
-	result.Timestamps = make([]float32, n)
-	timestamps := unsafe.Slice(p.timestamps, n)
-	for i := 0; i < n; i++ {
-		result.Timestamps[i] = float32(timestamps[i])
+	if p.durations != nil {
+		result.Durations = make([]float32, n)
+		durations := unsafe.Slice(p.durations, n)
+		for i := 0; i < n; i++ {
+			result.Durations[i] = float32(durations[i])
+		}
 	}
 	return result
 }

@@ -689,6 +689,14 @@ const SherpaOnnxOfflineRecognizerResult *SherpaOnnxGetOfflineStreamResult(
       r->timestamps = nullptr;
     }
 
+    if (!result.durations.empty() && result.durations.size() == r->count) {
+      r->durations = new float[r->count];
+      std::copy(result.durations.begin(), result.durations.end(),
+                r->durations);
+    } else {
+      r->durations = nullptr;
+    }
+
     r->tokens = tokens;
   } else {
     r->count = 0;
@@ -705,6 +713,7 @@ void SherpaOnnxDestroyOfflineRecognizerResult(
   if (r) {
     delete[] r->text;
     delete[] r->timestamps;
+    delete[] r->durations;
     delete[] r->tokens;
     delete[] r->tokens_arr;
     delete[] r->json;

@@ -614,6 +614,10 @@ SHERPA_ONNX_API typedef struct SherpaOnnxOfflineRecognizerResult {
   // It is NULL if the model does not support timestamps
   float *timestamps;
 
+    // Pointer to continuous memory which holds durations (in seconds) for each token
+    // It is NULL if the model does not support durations
+    float *durations;
+
   // number of entries in timestamps
   int32_t count;
 
@@ -631,6 +635,7 @@ SHERPA_ONNX_API typedef struct SherpaOnnxOfflineRecognizerResult {
    *     "text": "The recognition result",
    *     "tokens": [x, x, x],
    *     "timestamps": [x, x, x],
+   *     "durations": [x, x, x],
    *     "segment": x,
    *     "start_time": x,
    *     "is_final": true|false

@@ -36,6 +36,7 @@ static OfflineRecognitionResult Convert(
   OfflineRecognitionResult r;
   r.tokens.reserve(src.tokens.size());
   r.timestamps.reserve(src.timestamps.size());
+  r.durations.reserve(src.durations.size());
 
   std::string text;
   for (auto i : src.tokens) {
@@ -66,6 +67,11 @@ static OfflineRecognitionResult Convert(
     r.timestamps.push_back(time);
   }
 
+  // Copy durations (if present)
+  for (auto d : src.durations) {
+    r.durations.push_back(d * frame_shift_s);
+  }
+
   return r;
 }
 

@@ -397,6 +397,18 @@ std::string OfflineRecognitionResult::AsJsonString() const {
   os << "], ";
 
   os << "\""
+     << "durations"
+     << "\""
+     << ": ";
+  os << "[";
+  sep = "";
+  for (auto d : durations) {
+    os << sep << std::fixed << std::setprecision(2) << d;
+    sep = ", ";
+  }
+  os << "], ";
+
+  os << "\""
      << "tokens"
      << "\""
      << ":";

@@ -38,6 +38,9 @@ struct OfflineRecognitionResult {
   /// timestamps[i] records the time in seconds when tokens[i] is decoded.
   std::vector<float> timestamps;
 
+  /// durations[i] contains the duration (in seconds) for tokens[i] (TDT models only)
+  std::vector<float> durations;
+
   std::vector<int32_t> words;
 
   std::string AsJsonString() const;

@@ -19,6 +19,11 @@ struct OfflineTransducerDecoderResult {
   /// timestamps[i] contains the output frame index where tokens[i] is decoded.
   /// Note: The index is after subsampling
   std::vector<int32_t> timestamps;
+
+  /// durations[i] contains the duration for tokens[i] in output frames
+  /// (post-subsampling). It is converted to seconds by higher layers
+  /// (e.g., Convert() in offline-recognizer-transducer-impl.h).
+  std::vector<float> durations;
 };
 
 class OfflineTransducerDecoder {

@@ -130,23 +130,31 @@ static OfflineTransducerDecoderResult DecodeOneTDT(
       p_logit[blank_id] -= blank_penalty;
     }
 
-    auto y = static_cast<int32_t>(std::distance(
-        static_cast<const float *>(p_logit),
-        std::max_element(static_cast<const float *>(p_logit),
-                         static_cast<const float *>(p_logit) + vocab_size)));
+    int32_t output_size = shape.back();
+    int32_t num_durations = output_size - vocab_size;
 
-    skip = static_cast<int32_t>(std::distance(
-        static_cast<const float *>(p_logit) + vocab_size,
-        std::max_element(static_cast<const float *>(p_logit) + vocab_size,
-                         static_cast<const float *>(p_logit) + shape.back())));
+    // Split logits into token and duration logits
+    const float* token_logits = p_logit;
+    const float* duration_logits = p_logit + vocab_size;
 
-    if (skip == 0) {
-      skip = 1;
+    auto y = static_cast<int32_t>(std::distance(
+        token_logits,
+        std::max_element(token_logits, token_logits + vocab_size)));
+
+    skip = 1;
+    int32_t duration = 1;
+    if (num_durations > 0) {
+      duration = static_cast<int32_t>(std::distance(
+          duration_logits,
+          std::max_element(duration_logits, duration_logits + num_durations)));
+      skip = duration;
+      if (skip == 0) skip = 1;
     }
 
     if (y != blank_id) {
       ans.tokens.push_back(y);
       ans.timestamps.push_back(t);
+      ans.durations.push_back(duration);
 
       decoder_input_pair = BuildDecoderInput(y, model->Allocator());
 
@@ -155,7 +163,7 @@ static OfflineTransducerDecoderResult DecodeOneTDT(
                             std::move(decoder_input_pair.second),
                             std::move(decoder_output_pair.second));
     }
-  }  // for (int32_t t = 0; t < num_rows; ++t) {
+  }  // for (int32_t t = 0; t < num_rows; t += skip)
 
   return ans;
 }

@@ -33,17 +33,19 @@ static void PybindOfflineRecognitionResult(py::module *m) {  // NOLINT
                                                 self.text.size(), "ignore"));
           })
       .def_property_readonly("lang",
-                            [](const PyClass &self) { return self.lang; })
+         [](const PyClass &self) { return self.lang; })
       .def_property_readonly("emotion",
-                            [](const PyClass &self) { return self.emotion; })
+        [](const PyClass &self) { return self.emotion; })
       .def_property_readonly("event",
-                            [](const PyClass &self) { return self.event; })
+        [](const PyClass &self) { return self.event; })
       .def_property_readonly("tokens",
-                             [](const PyClass &self) { return self.tokens; })
+        [](const PyClass &self) { return self.tokens; })
       .def_property_readonly("words",
-                             [](const PyClass &self) { return self.words; })
-      .def_property_readonly(
-          "timestamps", [](const PyClass &self) { return self.timestamps; });
+        [](const PyClass &self) { return self.words; })
+      .def_property_readonly("timestamps",
+        [](const PyClass &self) { return self.timestamps; })
+      .def_property_readonly("durations",
+        [](const PyClass &self) { return self.durations; });
 }
 
 void PybindOfflineStream(py::module *m) {