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from __future__ import annotations
import gradio as gr
import numpy as np
import asyncio
from simuleval_transcoder import SimulevalTranscoder, logger
import time
from simuleval.utils.agent import build_system_from_dir
import torch
language_code_to_name = {
"cmn": "Mandarin Chinese",
"deu": "German",
"eng": "English",
"fra": "French",
"spa": "Spanish",
}
S2ST_TARGET_LANGUAGE_NAMES = language_code_to_name.values()
LANGUAGE_NAME_TO_CODE = {v: k for k, v in language_code_to_name.items()}
DEFAULT_TARGET_LANGUAGE = "English"
def build_agent(model_path, config_name=None):
agent = build_system_from_dir(
model_path, config_name=config_name,
)
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
agent.to(device, fp16=True)
return agent
agent = build_agent("models", "vad_s2st_sc_24khz_main.yaml")
transcoder = SimulevalTranscoder(
sample_rate=48_000,
debug=False,
buffer_limit=1,
)
def start_recording():
logger.debug(f"start_recording: starting transcoder")
transcoder.reset_states()
transcoder.start()
transcoder.close = False
def stop_recording():
transcoder.close = True
class MyState:
def __init__(self):
self.queue = asyncio.Queue()
self.close = False
s = MyState()
def process_incoming_bytes(audio):
logger.debug(f"process_bytes: incoming audio")
sample_rate, data = audio
transcoder.process_incoming_bytes(data.tobytes(), 'eng', sample_rate)
s.queue.put_nowait(audio)
def get_buffered_output():
speech_and_text_output = transcoder.get_buffered_output()
if speech_and_text_output is None:
logger.debug("No output from transcoder.get_buffered_output()")
return None, None, None
logger.debug(f"We DID get output from the transcoder!")
text = None
speech = None
if speech_and_text_output.speech_samples:
speech = (speech_and_text_output.speech_sample_rate, speech_and_text_output.speech_samples)
if speech_and_text_output.text:
text = speech_and_text_output.text
if speech_and_text_output.final:
text += "\n"
return speech, text, speech_and_text_output.final
def streaming_input_callback():
final = False
max_wait_s = 15
wait_s = 0
translated_text_state = ""
while not transcoder.close:
translated_wav_segment, translated_text, final = get_buffered_output()
if translated_wav_segment is None and translated_text is None:
time.sleep(0.3)
wait_s += 0.3
if wait_s >= max_wait_s:
transcoder.close = True
continue
wait_s = 0
if translated_wav_segment is not None:
sample_rate, audio_bytes = translated_wav_segment
print("output sample rate", sample_rate)
translated_wav_segment = sample_rate, np.array(audio_bytes)
else:
translated_wav_segment = bytes()
if translated_text is not None:
translated_text_state += " | " + str(translated_text)
stream_output_text = translated_text_state
if translated_text is not None:
print("translated:", translated_text_state)
yield [
translated_wav_segment,
stream_output_text,
translated_text_state,
]
def streaming_callback_dummy():
while not transcoder.close:
if s.queue.empty():
print("empty")
yield bytes()
time.sleep(0.3)
else:
print("audio")
audio = s.queue.get_nowait()
s.queue.task_done()
yield audio
def clear():
logger.debug(f"Clearing State")
return [bytes(), ""]
def blocks():
with gr.Blocks() as demo:
with gr.Row():
# TODO: add target language switching
target_language = gr.Dropdown(
label="Target language",
choices=S2ST_TARGET_LANGUAGE_NAMES,
value=DEFAULT_TARGET_LANGUAGE,
)
translated_text_state = gr.State("")
input_audio = gr.Audio(
label="Input Audio",
sources=["microphone"],
streaming=True,
)
output_translation_segment = gr.Audio(
label="Translated audio segment",
autoplay=True,
streaming=True,
)
# Output text segment
stream_output_text = gr.Textbox(label="Translated text")
input_audio.clear(
clear, None, [output_translation_segment, translated_text_state]
)
input_audio.start_recording(
clear, None, [output_translation_segment, translated_text_state]
).then(
start_recording
).then(
# streaming_callback_dummy, # TODO: autoplay works fine with streaming_callback_dummy
# None,
# output_translation_segment
streaming_input_callback,
None,
[
output_translation_segment,
stream_output_text,
translated_text_state,
],
)
input_audio.stop_recording(
stop_recording
)
input_audio.stream(
process_incoming_bytes, [input_audio], None
)
demo.launch(server_port=6010)
blocks()
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