Support TDNN models from the yesno recipe from icefall (#262)

python-api-examples/offline-decode-files.py

@@ -8,6 +8,7 @@ This file demonstrates how to use sherpa-onnx Python API to transcribe
 file(s) with a non-streaming model.
 
 (1) For paraformer
+
     ./python-api-examples/offline-decode-files.py  \
       --tokens=/path/to/tokens.txt \
       --paraformer=/path/to/paraformer.onnx \
@@ -20,6 +21,7 @@ file(s) with a non-streaming model.
       /path/to/1.wav
 
 (2) For transducer models from icefall
+
     ./python-api-examples/offline-decode-files.py  \
       --tokens=/path/to/tokens.txt \
       --encoder=/path/to/encoder.onnx \
@@ -56,9 +58,20 @@ python3 ./python-api-examples/offline-decode-files.py \
   ./sherpa-onnx-whisper-base.en/test_wavs/1.wav \
   ./sherpa-onnx-whisper-base.en/test_wavs/8k.wav
 
+(5) For tdnn models of the yesno recipe from icefall
+
+python3 ./python-api-examples/offline-decode-files.py \
+  --sample-rate=8000 \
+  --feature-dim=23 \
+  --tdnn-model=./sherpa-onnx-tdnn-yesno/model-epoch-14-avg-2.onnx \
+  --tokens=./sherpa-onnx-tdnn-yesno/tokens.txt \
+  ./sherpa-onnx-tdnn-yesno/test_wavs/0_0_0_1_0_0_0_1.wav \
+  ./sherpa-onnx-tdnn-yesno/test_wavs/0_0_1_0_0_0_1_0.wav \
+  ./sherpa-onnx-tdnn-yesno/test_wavs/0_0_1_0_0_1_1_1.wav
+
 Please refer to
 https://k2-fsa.github.io/sherpa/onnx/index.html
-to install sherpa-onnx and to download the pre-trained models
+to install sherpa-onnx and to download non-streaming pre-trained models
 used in this file.
 """
 import argparse
@@ -159,6 +172,13 @@ def get_args():
         help="Path to the model.onnx from NeMo CTC",
     )
 
+    parser.add_argument(
+        "--tdnn-model",
+        default="",
+        type=str,
+        help="Path to the model.onnx for the tdnn model of the yesno recipe",
+    )
+
     parser.add_argument(
         "--num-threads",
         type=int,
@@ -285,6 +305,7 @@ def main():
         assert len(args.nemo_ctc) == 0, args.nemo_ctc
         assert len(args.whisper_encoder) == 0, args.whisper_encoder
         assert len(args.whisper_decoder) == 0, args.whisper_decoder
+        assert len(args.tdnn_model) == 0, args.tdnn_model
 
         contexts = [x.strip().upper() for x in args.contexts.split("/") if x.strip()]
         if contexts:
@@ -311,6 +332,7 @@ def main():
         assert len(args.nemo_ctc) == 0, args.nemo_ctc
         assert len(args.whisper_encoder) == 0, args.whisper_encoder
         assert len(args.whisper_decoder) == 0, args.whisper_decoder
+        assert len(args.tdnn_model) == 0, args.tdnn_model
 
         assert_file_exists(args.paraformer)
 
@@ -326,6 +348,7 @@ def main():
     elif args.nemo_ctc:
         assert len(args.whisper_encoder) == 0, args.whisper_encoder
         assert len(args.whisper_decoder) == 0, args.whisper_decoder
+        assert len(args.tdnn_model) == 0, args.tdnn_model
 
         assert_file_exists(args.nemo_ctc)
 
@@ -339,6 +362,7 @@ def main():
             debug=args.debug,
         )
     elif args.whisper_encoder:
+        assert len(args.tdnn_model) == 0, args.tdnn_model
         assert_file_exists(args.whisper_encoder)
         assert_file_exists(args.whisper_decoder)
 
@@ -347,6 +371,20 @@ def main():
             decoder=args.whisper_decoder,
             tokens=args.tokens,
             num_threads=args.num_threads,
+            sample_rate=args.sample_rate,
+            feature_dim=args.feature_dim,
+            decoding_method=args.decoding_method,
+            debug=args.debug,
+        )
+    elif args.tdnn_model:
+        assert_file_exists(args.tdnn_model)
+
+        recognizer = sherpa_onnx.OfflineRecognizer.from_tdnn_ctc(
+            model=args.tdnn_model,
+            tokens=args.tokens,
+            sample_rate=args.sample_rate,
+            feature_dim=args.feature_dim,
+            num_threads=args.num_threads,
             decoding_method=args.decoding_method,
             debug=args.debug,
         )