init
Browse files
attach_speaker_embedding_s2s.py
CHANGED
@@ -14,7 +14,7 @@ hf_dataset = f"seamless-align-{direction}"
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dataset = load_dataset(f"{hf_org}/{hf_dataset}", f"subset_{dataset_id}", split="train")
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audio_loader = Audio()
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se_model = os.getenv("SE_MODEL", "metavoice")
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-
max_seq_length =
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min_seq_length = 50000
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if se_model == "metavoice":
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@@ -60,7 +60,7 @@ print(f"Num examples (after filtering): {len(dataset)}")
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def speaker_embedding(example):
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for side in sides:
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print(len(example[f"{side}.audio"]["array"]))
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embedding = speaker_embedder.get_speaker_embedding(
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example[f"{side}.audio"]["array"], example[f"{side}.audio"]["sampling_rate"]
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)
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dataset = load_dataset(f"{hf_org}/{hf_dataset}", f"subset_{dataset_id}", split="train")
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audio_loader = Audio()
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se_model = os.getenv("SE_MODEL", "metavoice")
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+
max_seq_length = 1000000
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min_seq_length = 50000
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if se_model == "metavoice":
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def speaker_embedding(example):
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for side in sides:
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# print(len(example[f"{side}.audio"]["array"]))
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embedding = speaker_embedder.get_speaker_embedding(
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example[f"{side}.audio"]["array"], example[f"{side}.audio"]["sampling_rate"]
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)
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