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clarify transcription parameter
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jfk.json
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jfk.json
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{"segments": [{"id": 0, "seek": 0, "start": 0.0, "end": 11.0, "text": " And so my fellow Americans, ask not what your country can do for you, ask what you can do for your country.", "tokens": [50364, 400, 370, 452, 7177, 6280, 11, 1029, 406, 437, 428, 1941, 393, 360, 337, 291, 11, 1029, 437, 291, 393, 360, 337, 428, 1941, 13, 50914], "temperature": 0.0, "avg_logprob": -0.20427462032863072, "compression_ratio": 1.3544303797468353, "no_speech_prob": 0.04382958635687828}], "language": "en", "text": " And so my fellow Americans, ask not what your country can do for you, ask what you can do for your country."}
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jfk.srt
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jfk.srt
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1
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00:00:00,000 --> 00:00:11,000
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And so my fellow Americans, ask not what your country can do for you, ask what you can do for your country.
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jfk.tsv
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jfk.tsv
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start end text
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0 11000 And so my fellow Americans, ask not what your country can do for you, ask what you can do for your country.
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jfk.txt
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jfk.txt
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And so my fellow Americans, ask not what your country can do for you, ask what you can do for your country.
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jfk.vtt
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jfk.vtt
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WEBVTT
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00:00.000 --> 00:11.000
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And so my fellow Americans, ask not what your country can do for you, ask what you can do for your country.
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@ -769,14 +769,15 @@ def audio_tensor(audio: Union[str, np.ndarray, torch.Tensor]) -> torch.Tensor:
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class MinimalTranscriber(Transcriber):
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exact: bool = True
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chlen: float = CHUNK_LENGTH
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# amount of time per chunk that is considered in-context
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contextualized: float = CHUNK_LENGTH
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async def process(self, stream: ArrayStream, **kw) -> dict:
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data = await stream.request(self.chlen, self.exact)
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data = await stream.request(CHUNK_LENGTH, self.exact)
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while data.shape[-1] > 0:
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self(data, stream.offset, True)
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t = (
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self.chlen
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self.contextualized
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- (stream.offset + data.shape[-1] - self.seek) / FRAMES_PER_SECOND
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+ CHUNK_LENGTH
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)
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