add tp inference in egs_modelscope

egs_modelscope/tp/speech_timestamp_prediction-v1-16k-offline/README.md

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+# ModelScope Model
+
+## How to finetune and infer using a pretrained ModelScope Model
+
+### Inference
+
+Or you can use the finetuned model for inference directly.
+
+- Setting parameters in `infer.py`
+    - <strong>audio_in:</strong> # support wav, url, bytes, and parsed audio format.
+    - <strong>output_dir:</strong> # If the input format is wav.scp, it needs to be set.
+
+- Then you can run the pipeline to infer with:
+```python
+    python infer.py
+```
+
+
+Modify inference related parameters in vad.yaml.
+
+- max_end_silence_time: The end-point silence duration  to judge the end of sentence, the parameter range is 500ms~6000ms, and the default value is 800ms
+- speech_noise_thres:  The balance of speech and silence scores, the parameter range is (-1,1)
+    - The value tends to -1, the greater probability of noise being judged as speech
+    - The value tends to 1, the greater probability of speech being judged as noise

egs_modelscope/tp/speech_timestamp_prediction-v1-16k-offline/infer.py

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+from modelscope.pipelines import pipeline
+from modelscope.utils.constant import Tasks
+
+inference_pipline = pipeline(
+    task=Tasks.speech_timestamp,
+    model='damo/speech_timestamp_prediction-v1-16k-offline',
+    output_dir='./tmp')
+
+rec_result = inference_pipline(
+    audio_in='https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_timestamps.wav',
+    text_in='一 个 东 太 平 洋 国 家 为 什 么 跑 到 西 太 平 洋 来 了 呢')
+print(rec_result)