add doc for vad asr models

generate-asr.py

@@ -112,6 +112,21 @@ see https://www.tablesgenerator.com/html_tables#
     <td class="tg-0lax">It supports both English and Chinese.</td>
     <td class="tg-0pky"><a href="https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20.tar.bz2">sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20.tar.bz2</a></td>
   </tr>
+  <tr>
+    <td class="tg-0pky">sherpa-onnx-x.y.z-arm64-v8a-asr-en-nemo_ctc_80ms.apk</td>
+    <td class="tg-0lax">It supports only English. It is converted from <a href="https://catalog.ngc.nvidia.com/orgs/nvidia/teams/nemo/models/stt_en_fastconformer_hybrid_large_streaming_80ms">STT En FastConformer Hybrid Transducer-CTC Large Streaming 80ms</a> from <a href="https://github.com/NVIDIA/NeMo/">NVIDIA/NeMo</a>. Note that only the CTC branch is used.</td>
+    <td class="tg-0pky"><a href="https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-nemo-streaming-fast-conformer-ctc-en-80ms.tar.bz2">sherpa-onnx-nemo-streaming-fast-conformer-ctc-en-80ms.tar.bz2</a></td>
+  </tr>
+  <tr>
+    <td class="tg-0pky">sherpa-onnx-x.y.z-arm64-v8a-asr-en-nemo_ctc_480ms.apk</td>
+    <td class="tg-0lax">It supports only English. It is converted from <a href="https://catalog.ngc.nvidia.com/orgs/nvidia/teams/nemo/models/stt_en_fastconformer_hybrid_large_streaming_480ms">STT En FastConformer Hybrid Transducer-CTC Large Streaming 480ms</a> from <a href="https://github.com/NVIDIA/NeMo/">NVIDIA/NeMo</a>. Note that only the CTC branch is used.</td>
+    <td class="tg-0pky"><a href="https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-nemo-streaming-fast-conformer-ctc-en-480ms.tar.bz2">sherpa-onnx-nemo-streaming-fast-conformer-ctc-en-480ms.tar.bz2</a></td>
+  </tr>
+  <tr>
+    <td class="tg-0pky">sherpa-onnx-x.y.z-arm64-v8a-asr-en-nemo_ctc_1040ms.apk</td>
+    <td class="tg-0lax">It supports only English. It is converted from <a href="https://catalog.ngc.nvidia.com/orgs/nvidia/teams/nemo/models/stt_en_fastconformer_hybrid_large_streaming_1040ms">STT En FastConformer Hybrid Transducer-CTC Large Streaming 1040ms</a> from <a href="https://github.com/NVIDIA/NeMo/">NVIDIA/NeMo</a>. Note that only the CTC branch is used.</td>
+    <td class="tg-0pky"><a href="https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-nemo-streaming-fast-conformer-ctc-en-1040ms.tar.bz2">sherpa-onnx-nemo-streaming-fast-conformer-ctc-en-1040ms.tar.bz2</a></td>
+  </tr>
   <tr>
     <td class="tg-0pky">sherpa-onnx-x.y.z-arm64-v8a-asr-fr-zipformer.apk</td>
     <td class="tg-0lax"><span style="font-weight:400;font-style:normal">It supports only French.</span></td>

generate-vad-asr.py

@@ -108,6 +108,30 @@ see https://www.tablesgenerator.com/html_tables#
   </tr>
 </thead>
 <tbody>
+  <tr>
+    <td class="tg-0pky">sherpa-onnx-x.y.z-arm64-v8a-vad_asr-be_de_en_es_fr_hr_it_pl_ru_uk-fast_conformer_ctc_20k.apk</td>
+    <td class="tg-0lax">It supports <span style="color:red;">10 languages</span>: Belarusian, German, English, Spanish, French, Croatian, Italian, Polish, Russian, and Ukrainian. It is converted from <a href="https://catalog.ngc.nvidia.com/orgs/nvidia/teams/nemo/models/stt_multilingual_fastconformer_hybrid_large_pc">STT Multilingual FastConformer Hybrid Transducer-CTC Large P&C</a> from <a href="https://github.com/NVIDIA/NeMo/">NVIDIA/NeMo</a>. Note that only the CTC branch is used. It is trained on ~20000 hours of data.</td>
+    <td class="tg-0pky"><a href="https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/silero_vad.onnx">silero_vad.onnx</a></td>
+    <td class="tg-0pky"><a href="https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-nemo-fast-conformer-transducer-be-de-en-es-fr-hr-it-pl-ru-uk-20k.tar.bz2">sherpa-onnx-nemo-fast-conformer-transducer-be-de-en-es-fr-hr-it-pl-ru-uk-20k.tar.bz2</a></td>
+  </tr>
+  <tr>
+    <td class="tg-0pky">sherpa-onnx-x.y.z-armeabi-v7a-vad_asr-en_des_es_fr-fast_conformer_ctc_14288.apk</td>
+    <td class="tg-0lax">It supports <span style="color:red;">4 languages</span>:  German, English, Spanish, and French . It is converted from <a href="https://catalog.ngc.nvidia.com/orgs/nvidia/teams/nemo/models/stt_multilingual_fastconformer_hybrid_large_pc_blend_eu">STT European FastConformer Hybrid Transducer-CTC Large P&C</a> from <a href="https://github.com/NVIDIA/NeMo/">NVIDIA/NeMo</a>. Note that only the CTC branch is used. It is trained on 14288 hours of data.</td>
+    <td class="tg-0pky"><a href="https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/silero_vad.onnx">silero_vad.onnx</a></td>
+    <td class="tg-0pky"><a href="https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-nemo-fast-conformer-transducer-en-de-es-fr-14288.tar.bz2">sherpa-onnx-nemo-fast-conformer-transducer-en-de-es-fr-14288.tar.bz2</a></td>
+  </tr>
+  <tr>
+    <td class="tg-0pky">sherpa-onnx-x.y.z-arm64-v8a-vad_asr-es-fast_conformer_ctc_1424.apk</td>
+    <td class="tg-0lax">It supports only Spanish. It is converted from <a href="https://catalog.ngc.nvidia.com/orgs/nvidia/teams/nemo/models/stt_es_fastconformer_hybrid_large_pc">STT Es FastConformer Hybrid Transducer-CTC Large P&C</a> from <a href="https://github.com/NVIDIA/NeMo/">NVIDIA/NeMo</a>. Note that only the CTC branch is used. It is trained on 1424 hours of data.</td>
+    <td class="tg-0pky"><a href="https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/silero_vad.onnx">silero_vad.onnx</a></td>
+    <td class="tg-0pky"><a href="https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-nemo-fast-conformer-transducer-es-1424.tar.bz2">sherpa-onnx-nemo-fast-conformer-transducer-es-1424.tar.bz2</a></td>
+  </tr>
+  <tr>
+    <td class="tg-0pky">sherpa-onnx-x.y.z-arm64-v8a-vad_asr-en-fast_conformer_ctc_24500.apk</td>
+    <td class="tg-0lax">It supports only English. It is converted from <a href="https://catalog.ngc.nvidia.com/orgs/nvidia/teams/nemo/models/stt_en_fastconformer_hybrid_large_pc">STT En FastConformer Hybrid Transducer-CTC Large P&C</a> from <a href="https://github.com/NVIDIA/NeMo/">NVIDIA/NeMo</a>. Note that only the CTC branch is used. It is trained on 8500 hours of data.</td>
+    <td class="tg-0pky"><a href="https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/silero_vad.onnx">silero_vad.onnx</a></td>
+    <td class="tg-0pky"><a href="https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-nemo-fast-conformer-transducer-en-24500.tar.bz2">sherpa-onnx-nemo-fast-conformer-transducer-en-24500.tar.bz2</a></td>
+  </tr>
   <tr>
     <td class="tg-0pky">sherpa-onnx-x.y.z-arm64-v8a-vad_asr-zh-zipformer.apk</td>
     <td class="tg-0lax">It supports only Chinese.</td>