FunASR/runtime/python/onnxruntime/demo_contextual_paraformer.py
Yabin Li 702ec03ad8
Dev new (#1065)
* add hotword for deploy_tools

* Support wfst decoder and contextual biasing (#1039)

* Support wfst decoder and contextual biasing

* Turn on fstbin compilation

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Co-authored-by: gongbo.gb <gongbo.gb@alibaba-inc.com>

* mv funasr/runtime runtime

* Fix crash caused by OOV in hotwords list

* funasr infer

* funasr infer

* funasr infer

* funasr infer

* funasr infer

* fix some bugs about fst hotword; support wfst for websocket server and clients; mv runtime out of funasr; modify relative docs

* del onnxruntime/include/gflags

* update tensor.h

* update run_server.sh

* update deploy tools

* update deploy tools

* update websocket-server

* update funasr-wss-server

* Remove self loop propagation

* Update websocket_protocol_zh.md

* Update websocket_protocol_zh.md

* update hotword protocol

* author zhaomingwork: change hotwords for h5 and java

* update hotword protocol

* catch exception for json_fst_hws

* update hotword on message

* update onnx benchmark for ngram&hotword

* update docs

* update funasr-wss-serve

* add NONE for LM_DIR

* update docs

* update run_server.sh

* add whats-new

* modify whats-new

* update whats-new

* update whats-new

* Support decoder option for beam searching

* update benchmark_onnx_cpp

* Support decoder option for websocket

* fix bug of CompileHotwordEmbedding

* update html client

* update docs

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Co-authored-by: gongbo.gb <35997837+aibulamusi@users.noreply.github.com>
Co-authored-by: gongbo.gb <gongbo.gb@alibaba-inc.com>
Co-authored-by: 游雁 <zhifu.gzf@alibaba-inc.com>
2023-11-07 18:34:29 +08:00

13 lines
497 B
Python

from funasr_onnx import ContextualParaformer
from pathlib import Path
model_dir = "./export/damo/speech_paraformer-large-contextual_asr_nat-zh-cn-16k-common-vocab8404"
model = ContextualParaformer(model_dir, batch_size=1)
wav_path = ['{}/.cache/modelscope/hub/damo/speech_paraformer-large-contextual_asr_nat-zh-cn-16k-common-vocab8404/example/asr_example.wav'.format(Path.home())]
hotwords = '随机热词 各种热词 魔搭 阿里巴巴 仏'
result = model(wav_path, hotwords)
print(result)