StreamSpeech / SimulEval /examples /speech_to_speech /english_counter_agent.py
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init
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from simuleval.utils import entrypoint
from simuleval.data.segments import SpeechSegment
from simuleval.agents import SpeechToSpeechAgent
from simuleval.agents.actions import WriteAction, ReadAction
from fairseq.checkpoint_utils import load_model_ensemble_and_task_from_hf_hub
from fairseq.models.text_to_speech.hub_interface import TTSHubInterface
class TTSModel:
def __init__(self):
models, cfg, task = load_model_ensemble_and_task_from_hf_hub(
"facebook/fastspeech2-en-ljspeech",
arg_overrides={"vocoder": "hifigan", "fp16": False},
)
TTSHubInterface.update_cfg_with_data_cfg(cfg, task.data_cfg)
self.tts_generator = task.build_generator(models, cfg)
self.tts_task = task
self.tts_model = models[0]
self.tts_model.to("cpu")
self.tts_generator.vocoder.to("cpu")
def synthesize(self, text):
sample = TTSHubInterface.get_model_input(self.tts_task, text)
if sample["net_input"]["src_lengths"][0] == 0:
return [], 0
for key in sample["net_input"].keys():
if sample["net_input"][key] is not None:
sample["net_input"][key] = sample["net_input"][key].to("cpu")
wav, rate = TTSHubInterface.get_prediction(
self.tts_task, self.tts_model, self.tts_generator, sample
)
wav = wav.tolist()
return wav, rate
@entrypoint
class EnglishSpeechCounter(SpeechToSpeechAgent):
"""
Incrementally feed text to this offline Fastspeech2 TTS model,
with a minimum numbers of phonemes every chunk.
"""
def __init__(self, args):
super().__init__(args)
self.wait_seconds = args.wait_seconds
self.tts_model = TTSModel()
@staticmethod
def add_args(parser):
parser.add_argument("--wait-seconds", default=1, type=int)
def policy(self):
length_in_seconds = round(
len(self.states.source) / self.states.source_sample_rate
)
if not self.states.source_finished and length_in_seconds < self.wait_seconds:
return ReadAction()
samples, fs = self.tts_model.synthesize(f"{length_in_seconds} mississippi")
# A SpeechSegment has to be returned for speech-to-speech translation system
return WriteAction(
SpeechSegment(
content=samples,
sample_rate=fs,
finished=self.states.source_finished,
),
finished=self.states.source_finished,
)