whisper kotoba-shisper-v1.0

import torch
from transformers import AutoModelForSpeechSeq2Seq, AutoProcessor, pipeline

# config
model_id = "kotoba-tech/kotoba-whisper-v1.0"
torch_dtype = torch.float16 if torch.cuda.is_available() else torch.float32
device = "cuda:0" if torch.cuda.is_available() else "cpu"

# load model
model = AutoModelForSpeechSeq2Seq.from_pretrained(model_id, torch_dtype=torch_dtype, low_cpu_mem_usage=True, use_safetensors=True)
model.to(device)
processor = AutoProcessor.from_pretrained(model_id)

pipe = pipeline(
    "automatic-speech-recognition",
    model=model,
    tokenizer=processor.tokenizer,
    feature_extractor=processor.feature_extractor,
    max_new_tokens=128,
    torch_dtype=torch_dtype,
    device=device,
)

audio_file = "./abc.mp3"

result = pipe(audio_file)
print(result["text"])

#音声ファイルから日本語を抽出

#ここではabc.mp3を用意

import torch
from transformers import AutoModelForSpeechSeq2Seq, AutoProcessor, pipeline
from datasets import load_dataset, Audio

# config
model_id = "kotoba-tech/kotoba-whisper-v1.0"
torch_dtype = torch.float16 if torch.cuda.is_available() else torch.float32
device = "cuda:0" if torch.cuda.is_available() else "cpu"

# load model
model = AutoModelForSpeechSeq2Seq.from_pretrained(model_id, torch_dtype=torch_dtype, low_cpu_mem_usage=True, use_safetensors=True)
model.to(device)
processor = AutoProcessor.from_pretrained(model_id)
pipe = pipeline(
    "automatic-speech-recognition",
    model=model,
    tokenizer=processor.tokenizer,
    feature_extractor=processor.feature_extractor,
    max_new_tokens=128,
    torch_dtype=torch_dtype,
    device=device,
)


# load sample audio & downsample to 16kHz
dataset = load_dataset("japanese-asr/ja_asr.reazonspeech_test", split="test")
dataset = dataset.cast_column("audio", Audio(sampling_rate=16000))
sample = dataset[0]["audio"]

# run inference
result = pipe(sample)
print(result["text"])

日本語音声認識に特化したWhisperである kotoba-whisper-v1.0を早速試してみた | DevelopersIO

はじめに昨日公開された日本語音声認識に特化した「Kotoba-Whisper」のkotoba-whisper-v1.0を試してみました。本モデルは、OpenAIの「Whisper large-v3」を教師モデルとして …