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from parler_tts import ParlerTTSForConditionalGeneration
from transformers import AutoTokenizer
import soundfile as sf
import pygame
from dora import DoraStatus
model = ParlerTTSForConditionalGeneration.from_pretrained(
"parler-tts/parler_tts_mini_v0.1"
).to("cuda:0")
tokenizer = AutoTokenizer.from_pretrained("parler-tts/parler_tts_mini_v0.1")
pygame.mixer.init()
input_ids = tokenizer(
"A female speaker with a slightly low-pitched voice delivers her words quite expressively, in a very confined sounding environment with clear audio quality. She speaks very fast.",
return_tensors="pt",
).input_ids.to("cuda:0")
class Operator:
def on_event(
self,
dora_event,
send_output,
):
if dora_event["type"] == "INPUT":
generation = model.generate(
max_new_tokens=300,
input_ids=input_ids,
prompt_input_ids=tokenizer(
dora_event["value"][0].as_py(), return_tensors="pt"
).input_ids.to("cuda:0"),
)
print(dora_event["value"][0].as_py(), flush=True)
sf.write(
f"parler_tts_out.wav",
generation.cpu().numpy().squeeze(),
model.config.sampling_rate,
)
while pygame.mixer.get_busy():
pass
pygame.mixer.music.load(f"parler_tts_out.wav")
pygame.mixer.music.play()
return DoraStatus.CONTINUE
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