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Project description
asrp
ASR text preprocessing utility
install
pip install asrp
usage - preprocess
input: dictionary, with key sentence
output: preprocessed result, inplace handling.
import asrp
batch_data = {
'sentence': "I'm fine, thanks."
}
asrp.fun_en(batch_data)
dynamic loading
import asrp
batch_data = {
'sentence': "I'm fine, thanks."
}
preprocessor = getattr(asrp, 'fun_en')
preprocessor(batch_data)
usage - evaluation
import asrp
targets = ['HuggingFace is great!', 'Love Transformers!', 'Let\'s wav2vec!']
preds = ['HuggingFace is awesome!', 'Transformers is powerful.', 'Let\'s finetune wav2vec!']
print("chunk size WER: {:2f}".format(100 * asrp.chunked_wer(targets, preds, chunk_size=None)))
print("chunk size CER: {:2f}".format(100 * asrp.chunked_cer(targets, preds, chunk_size=None)))
usage - hubertcode
import asrp
hc = asrp.HubertCode("facebook/hubert-large-ll60k", './km_feat_100_layer_20', 20)
hc('voice file path')
usage - code2speech
import asrp
code = [] # discrete unit
# download tts checkpoint and waveglow_checkpint from https://github.com/pytorch/fairseq/tree/main/examples/textless_nlp/gslm/unit2speech
cs = asrp.Code2Speech(tts_checkpoint='./tts_checkpoint_best.pt', waveglow_checkpint='waveglow_256channels_new.pt')
cs(code)
# play on notebook
import IPython.display as ipd
ipd.Audio(data=cs(code), autoplay=False, rate=cs.sample_rate)
usage - liveASR
- modify from https://github.com/oliverguhr/wav2vec2-live
from asrp.live import LiveHFSpeech
english_model = "voidful/wav2vec2-xlsr-multilingual-56"
asr = LiveHFSpeech(english_model, device_name="default")
asr.start()
try:
while True:
text, sample_length, inference_time = asr.get_last_text()
print(f"{sample_length:.3f}s"
+ f"\t{inference_time:.3f}s"
+ f"\t{text}")
except KeyboardInterrupt:
asr.stop()
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