Add JavaScript API (node-addon) for Google MedAsr model (#2955)

Author: csukuangfj

.github/scripts/test-nodejs-addon-npm.sh

@@ -10,6 +10,16 @@ arch=$(node -p "require('os').arch()")
 platform=$(node -p "require('os').platform()")
 node_version=$(node -p "process.versions.node.split('.')[0]")
 
+echo "----------non-streaming ASR Google MedASR CTC----------"
+
+wget https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-medasr-ctc-en-int8-2025-12-25.tar.bz2
+tar xvf sherpa-onnx-medasr-ctc-en-int8-2025-12-25.tar.bz2
+rm sherpa-onnx-medasr-ctc-en-int8-2025-12-25.tar.bz2
+
+node ./test_asr_non_streaming_medasr_ctc.js
+
+rm -rf sherpa-onnx-medasr-ctc-en-int8-2025-12-25
+
 echo "----------non-streaming ASR Omnilingual ASR CTC----------"
 
 curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-omnilingual-asr-1600-languages-300M-ctc-int8-2025-11-12.tar.bz2

harmony-os/SherpaOnnxHar/sherpa_onnx/src/main/cpp/non-streaming-asr.cc

@@ -94,6 +94,22 @@ GetOfflineOmnilingualAsrCtcModelConfig(Napi::Object obj) {
   return c;
 }
 
+static SherpaOnnxOfflineMedAsrCtcModelConfig GetOfflineMedAsrCtcModelConfig(
+    Napi::Object obj) {
+  SherpaOnnxOfflineMedAsrCtcModelConfig c;
+  memset(&c, 0, sizeof(c));
+
+  if (!obj.Has("medasr") || !obj.Get("medasr").IsObject()) {
+    return c;
+  }
+
+  Napi::Object o = obj.Get("medasr").As<Napi::Object>();
+
+  SHERPA_ONNX_ASSIGN_ATTR_STR(model, model);
+
+  return c;
+}
+
 static SherpaOnnxOfflineDolphinModelConfig GetOfflineDolphinModelConfig(
     Napi::Object obj) {
   SherpaOnnxOfflineDolphinModelConfig c;
@@ -260,6 +276,7 @@ static SherpaOnnxOfflineModelConfig GetOfflineModelConfig(Napi::Object obj) {
   c.canary = GetOfflineCanaryModelConfig(o);
   c.wenet_ctc = GetOfflineWenetCtcModelConfig(o);
   c.omnilingual = GetOfflineOmnilingualAsrCtcModelConfig(o);
+  c.medasr = GetOfflineMedAsrCtcModelConfig(o);
 
   SHERPA_ONNX_ASSIGN_ATTR_STR(tokens, tokens);
   SHERPA_ONNX_ASSIGN_ATTR_INT32(num_threads, numThreads);
@@ -354,6 +371,7 @@ static void FreeConfig(const SherpaOnnxOfflineRecognizerConfig &c) {
 
   SHERPA_ONNX_DELETE_C_STR(c.model_config.wenet_ctc.model);
   SHERPA_ONNX_DELETE_C_STR(c.model_config.omnilingual.model);
+  SHERPA_ONNX_DELETE_C_STR(c.model_config.medasr.model);
 
   SHERPA_ONNX_DELETE_C_STR(c.model_config.tokens);
   SHERPA_ONNX_DELETE_C_STR(c.model_config.provider);

nodejs-addon-examples/README.md

@@ -126,6 +126,7 @@ The following tables list the examples in this folder.
 |[./test_asr_non_streaming_nemo_ctc.js](./test_asr_non_streaming_nemo_ctc.js)|Non-streaming speech recognition from a file using a [NeMo](https://github.com/NVIDIA/NeMo) CTC model with greedy search|
 |[./test_asr_non_streaming_wenet_ctc.js](./test_asr_non_streaming_wenet_ctc.js)|Non-streaming speech recognition from a file using a [u2pp_conformer_yue](https://huggingface.co/ASLP-lab/WSYue-ASR/tree/main/u2pp_conformer_yue) CTC model with greedy search|
 |[./test_asr_non_streaming_omnilingual_asr_ctc.js](./test_asr_non_streaming_omnilingual_asr_ctc.js)|Non-streaming speech recognition from a file using a [Omnilingual-ASR](https://github.com/facebookresearch/omnilingual-asr) CTC model with greedy search|
+|[./test_asr_non_streaming_medasr_ctc.js](./test_asr_non_streaming_medasr_ctc.js)|Non-streaming speech recognition from a file using a [Google MedASR](https://github.com/google-health/medasr) CTC model with greedy search|
 |[./test_asr_non_streaming_nemo_canary.js](./test_asr_non_streaming_nemo_canary.js)|Non-streaming speech recognition from a file using a [NeMo](https://github.com/NVIDIA/NeMo) [Canary](https://k2-fsa.github.io/sherpa/onnx/nemo/canary.html#sherpa-onnx-nemo-canary-180m-flash-en-es-de-fr-int8-english-spanish-german-french) model|
 |[./test_asr_non_streaming_zipformer_ctc.js](./test_asr_non_streaming_zipformer_ctc.js)|Non-streaming speech recognition from a file using a Zipformer CTC model with greedy search|
 |[./test_asr_non_streaming_nemo_parakeet_tdt_v2.js](./test_asr_non_streaming_nemo_parakeet_tdt_v2.js)|Non-streaming speech recognition from a file using a [NeMo](https://github.com/NVIDIA/NeMo) [parakeet-tdt-0.6b-v2](https://k2-fsa.github.io/sherpa/onnx/pretrained_models/offline-transducer/nemo-transducer-models.html#sherpa-onnx-nemo-parakeet-tdt-0-6b-v2-int8-english) model with greedy search|
@@ -428,6 +429,16 @@ npm install naudiodon2
 node ./test_vad_asr_non_streaming_nemo_ctc_microphone.js
 ```
 
+### Non-streaming speech recognition with Google MedASR CTC models
+
+```bash
+wget https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-medasr-ctc-en-int8-2025-12-25.tar.bz2
+tar xvf sherpa-onnx-medasr-ctc-en-int8-2025-12-25.tar.bz2
+rm sherpa-onnx-medasr-ctc-en-int8-2025-12-25.tar.bz2
+
+node ./test_asr_non_streaming_medasr_ctc.js
+```
+
 ### Non-streaming speech recognition with Omnilingual ASR CTC models
 
 ```bash

nodejs-addon-examples/test_asr_non_streaming_medasr_ctc.js

@@ -0,0 +1,46 @@
+// Copyright (c)  2025  Xiaomi Corporation
+const sherpa_onnx = require('sherpa-onnx-node');
+
+// Please download test files from
+// https://github.com/k2-fsa/sherpa-onnx/releases/tag/asr-models
+const config = {
+  'featConfig': {
+    'sampleRate': 16000,
+    'featureDim': 80,
+  },
+  'modelConfig': {
+    'medasr': {
+      'model': './sherpa-onnx-medasr-ctc-en-int8-2025-12-25/model.int8.onnx',
+    },
+    'tokens': './sherpa-onnx-medasr-ctc-en-int8-2025-12-25/tokens.txt',
+    'numThreads': 2,
+    'provider': 'cpu',
+    'debug': 1,
+  }
+};
+
+const waveFilename =
+    './sherpa-onnx-medasr-ctc-en-int8-2025-12-25/test_wavs/0.wav';
+
+const recognizer = new sherpa_onnx.OfflineRecognizer(config);
+console.log('Started')
+let start = Date.now();
+const stream = recognizer.createStream();
+const wave = sherpa_onnx.readWave(waveFilename);
+stream.acceptWaveform({sampleRate: wave.sampleRate, samples: wave.samples});
+
+recognizer.decode(stream);
+const result = recognizer.getResult(stream);
+let stop = Date.now();
+console.log('Done')
+
+const elapsed_seconds = (stop - start) / 1000;
+const duration = wave.samples.length / wave.sampleRate;
+const real_time_factor = elapsed_seconds / duration;
+console.log('Wave duration', duration.toFixed(3), 'seconds')
+console.log('Elapsed', elapsed_seconds.toFixed(3), 'seconds')
+console.log(
+    `RTF = ${elapsed_seconds.toFixed(3)}/${duration.toFixed(3)} =`,
+    real_time_factor.toFixed(3))
+console.log(waveFilename)
+console.log('result\n', result)