add distill whisper results (k2-fsa#1648)

egs/multi_zh-hans/ASR/RESULTS.md

@@ -6,10 +6,11 @@
 
 Character Error Rates (CERs) listed below are produced by the checkpoint of the second epoch using greedy search.
 
-| Datasets | alimeeting | alimeeting | aishell-1 | aishell-1 | aishell-2 | aishell-2 | aishell-4 | magicdata | magicdata | kespeech-asr | kespeech-asr | kespeech-asr | WenetSpeech  |
-|--------------------------------|-------------------|--------------|----------------|-------------|------------------|-------------|------------------|------------------|-------------|-----------------------|-----------------------|-------------|-------------------|
-|  Split |           eval| test | dev | test | dev| test | test      | dev| test | dev phase1 | dev phase2 | test | test meeting |
-| Greedy Search |  23.22 | 28.24 | 0.61 | 0.66 | 2.67 | 2.80 | 16.61 | 2.56 | 2.21 | 4.73 | 1.90 | 5.98 |                    8.13 |
+|Model| Datasets | alimeeting | alimeeting | aishell-1 | aishell-1 | aishell-2 | aishell-2 | aishell-4 | magicdata | magicdata | kespeech-asr | kespeech-asr | kespeech-asr | WenetSpeech  |
+|-|--------------------------------|-------------------|--------------|----------------|-------------|------------------|-------------|------------------|------------------|-------------|-----------------------|-----------------------|-------------|-------------------|
+| | Split |           eval| test | dev | test | dev| test | test      | dev| test | dev phase1 | dev phase2 | test | test meeting |
+|whisper-large-v2-ft |Greedy Search |  23.22 | 28.24 | 0.61 | 0.66 | 2.67 | 2.80 | 16.61 | 2.56 | 2.21 | 4.73 | 1.90 | 5.98 |                    8.13 |
+|whisper-large-v2-ft-distill |Greedy Search | 24.91  | 26.73 | 0.91 | 0.94 | 2.71 | 2.98 | 17.65 | 2.81 | 2.47 | 5.16 | 2.10 | 6.27 |   8.34                  |
 
 Command for training is:
 ```bash

egs/speechio/ASR/RESULTS.md

@@ -17,12 +17,15 @@
 | 7 | aispeech_api_zh | 3.62% | 2023.12 |
 | 8 | **whisper-large-ft-v1** | **4.32%** | 2024.04 |
 | 9 | **whisper-large-ft-v0.5** | **4.60%** | 2024.04 |
-| 10 | **zipformer (70Mb)** | **6.17%** | 2023.10 |
-| 11 | **whisper-large-ft-v0**  | **6.34%** | 2023.03 |
-| 12 | baidu_pro_api_zh | 7.29% | 2023.12 |
+| 10 | **whisper-large-ft-v1-distill** | **4.71%** | 2024.04 |
+| 11 | **zipformer (70Mb)** | **6.17%** | 2023.10 |
+| 12 | **whisper-large-ft-v0**  | **6.34%** | 2023.03 |
+| 13 | baidu_pro_api_zh | 7.29% | 2023.12 |
 
 Note: Above API results are from [SPEECHIO](https://github.com/SpeechColab/Leaderboard). All results used the default [normalize method.](https://github.com/SpeechColab/Leaderboard/blob/master/utils/benchmark.sh#L67)
 
+For  **whisper-large-ft-v1-distill**, instead of actually using distillation loss for training, the model structure and parameter initialization method from the [distill-whisper](https://arxiv.org/abs/2311.00430) paper were adopted: only the first and last layers of the decoder were retained.
+
 <details><summary> Detail all models </summary><p>
 
 | Model | Training Set | Note |
@@ -31,7 +34,7 @@ Note: Above API results are from [SPEECHIO](https://github.com/SpeechColab/Leade
 |[whisper-large-ft-v0](https://huggingface.co/yuekai/icefall_asr_wenetspeech_whisper/tree/main/exp_large_v2)| wenetspeech | greedy_search, 3 epochs|
 |[whisper-large-ft-v0.5](https://huggingface.co/yuekai/icefall_asr_wenetspeech_whisper/blob/main/epoch-2-avg-5.pt)| wenetspeech(updated) | [wenetspeech update method](https://github.com/k2-fsa/icefall/blob/master/egs/wenetspeech/ASR/local/fix_manifest.py), greedy_search, 2 epochs |
 |[whisper-large-ft-v1](https://huggingface.co/yuekai/icefall_asr_multi-hans-zh_whisper/tree/main/v1.1)|wenetspeech(updated), other multi-hans-zh exclude datatang 200h|[wenetspeech update method](https://github.com/k2-fsa/icefall/blob/master/egs/wenetspeech/ASR/local/fix_manifest.py), greedy search, 3 epochs|
-
+|[whisper-large-ft-v1-distill](https://huggingface.co/yuekai/icefall_asr_multi-hans-zh_whisper/tree/main/v1-distill)|wenetspeech(updated), other multi-hans-zh exclude datatang 200h|[wenetspeech update method](https://github.com/k2-fsa/icefall/blob/master/egs/wenetspeech/ASR/local/fix_manifest.py), greedy search, 6 epochs|
 </details>
 
 

egs/speechio/ASR/whisper/decode.py

@@ -58,6 +58,7 @@
 from multi_dataset import MultiDataset
 from tn.chinese.normalizer import Normalizer
 from whisper.normalizers import BasicTextNormalizer
+from whisper_decoder_forward_monkey_patch import replace_whisper_decoder_forward
 from whisper_encoder_forward_monkey_patch import replace_whisper_encoder_forward
 from zhconv import convert
 
@@ -215,7 +216,7 @@ def get_parser():
         "--model-name",
         type=str,
         default="large-v2",
-        choices=["large-v2", "large-v3", "medium", "small", "base", "tiny"],
+        choices=["large-v2", "large-v3", "medium", "base", "small", "tiny"],
         help="""The model name to use.
         """,
     )
@@ -227,6 +228,13 @@ def get_parser():
         help="replace whisper encoder forward method to remove input length restriction",
     )
 
+    parser.add_argument(
+        "--use-distill-whisper",
+        type=str2bool,
+        default=False,
+        help="Whether to use architecture of distill whisper.",
+    )
+
     return parser
 
 
@@ -431,6 +439,8 @@ def main():
 
     if params.remove_whisper_encoder_input_length_restriction:
         replace_whisper_encoder_forward()
+    if params.use_distill_whisper:
+        replace_whisper_decoder_forward()
     model = whisper.load_model(params.model_name, "cpu")
     if params.epoch > 0:
         if params.avg > 1:

egs/speechio/ASR/whisper/whisper_decoder_forward_monkey_patch.py

@@ -0,0 +1 @@
+../../../multi_zh-hans/ASR/whisper/whisper_decoder_forward_monkey_patch.py