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from parler_tts import ParlerTTSForConditionalGeneration |
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from transformers import AutoTokenizer |
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import soundfile as sf |
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import pygame |
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from dora import DoraStatus |
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model = ParlerTTSForConditionalGeneration.from_pretrained( |
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"ylacombe/parler-tts-mini-jenny-30H" |
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).to("cuda:0") |
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tokenizer = AutoTokenizer.from_pretrained("ylacombe/parler-tts-mini-jenny-30H") |
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pygame.mixer.init() |
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input_ids = tokenizer( |
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"Jenny delivers her words quite expressively, in a very confined sounding environment with clear audio quality.", |
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return_tensors="pt", |
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).input_ids.to("cuda:0") |
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class Operator: |
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def on_event( |
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self, |
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dora_event, |
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send_output, |
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): |
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if dora_event["type"] == "INPUT": |
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generation = model.generate( |
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input_ids=input_ids, |
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min_new_tokens=100, |
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prompt_input_ids=tokenizer( |
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dora_event["value"][0].as_py(), return_tensors="pt" |
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).input_ids.to("cuda:0"), |
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) |
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print(dora_event["value"][0].as_py(), flush=True) |
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sf.write( |
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f"parler_tts_out.wav", |
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generation.cpu().numpy().squeeze(), |
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model.config.sampling_rate, |
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) |
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pygame.mixer.music.load(f"parler_tts_out.wav") |
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pygame.mixer.music.play() |
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while pygame.mixer.get_busy(): |
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pass |
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return DoraStatus.CONTINUE |
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