makaveli10
291 lines
10 KiB
Python
291 lines
10 KiB
Python
import websockets
|
|
import pickle, struct, time, pyaudio
|
|
import threading
|
|
import os, json
|
|
import wave
|
|
import textwrap
|
|
|
|
import logging
|
|
logging.basicConfig(level = logging.INFO)
|
|
|
|
from collections import deque
|
|
from dataclasses import dataclass
|
|
|
|
import torch
|
|
import numpy as np
|
|
from websockets.sync import server
|
|
from websockets.sync.server import serve
|
|
from transcriber import WhisperModel
|
|
|
|
|
|
clients = {}
|
|
SERVER_READY = "SERVER_READY"
|
|
|
|
def recv_audio(websocket):
|
|
"""
|
|
Receive audio chunks from client in an infinite loop.
|
|
"""
|
|
global clients
|
|
options = websocket.recv()
|
|
options = json.loads(options)
|
|
client = ServeClient(
|
|
websocket,
|
|
multilingual=options["multilingual"],
|
|
language=options["language"],
|
|
task=options["task"]
|
|
)
|
|
|
|
clients[websocket] = client
|
|
|
|
while True:
|
|
try:
|
|
frame_data = websocket.recv()
|
|
frame_np = np.frombuffer(frame_data, np.float32)
|
|
clients[websocket].add_frames(frame_np)
|
|
|
|
except Exception as e:
|
|
clients[websocket].cleanup()
|
|
clients.pop(websocket)
|
|
logging.info("Connection Closed.")
|
|
break
|
|
|
|
|
|
class ServeClient:
|
|
RATE = 16000
|
|
def __init__(self, websocket, task="transcribe", device=None, multilingual=False, language=None):
|
|
self.data = b""
|
|
self.frames = b""
|
|
self.language = language
|
|
self.task = task
|
|
self.transcriber = WhisperModel(
|
|
"small" if multilingual else "small.en",
|
|
device=device if device else "cuda",
|
|
compute_type="float16",
|
|
local_files_only=False,
|
|
)
|
|
|
|
# voice activity detection model
|
|
self.vad_model, _ = torch.hub.load(repo_or_dir='snakers4/silero-vad',
|
|
model='silero_vad',
|
|
force_reload=True,
|
|
onnx=True
|
|
)
|
|
self.vad_threshold = 0.4
|
|
|
|
self.timestamp_offset = 0.0
|
|
self.frames_np = None
|
|
self.frames_offset = 0.0
|
|
self.text = []
|
|
self.current_out = ''
|
|
self.prev_out = ''
|
|
self.t_start=None
|
|
self.exit = False
|
|
self.same_output_threshold = 0
|
|
self.show_prev_out_thresh = 5 # if pause(no output from whisper) show previous output for 5 seconds
|
|
self.add_pause_thresh = 3 # add a blank to segment list as a pause(no speech) for 3 seconds
|
|
self.transcript = []
|
|
self.send_last_n_segments = 10
|
|
|
|
# text formatting
|
|
self.wrapper = textwrap.TextWrapper(width=50)
|
|
self.pick_previous_segments = 2
|
|
|
|
# threading
|
|
self.websocket = websocket
|
|
self.trans_thread = threading.Thread(target=self.speech_to_text)
|
|
self.trans_thread.start()
|
|
self.websocket.send(json.dumps(SERVER_READY))
|
|
|
|
def fill_output(self, output):
|
|
"""
|
|
Format output with current and previous complete segments
|
|
into two lines of 50 characters.
|
|
|
|
Args:
|
|
output(str): current incomplete segment
|
|
|
|
Returns:
|
|
transcription wrapped in two lines
|
|
"""
|
|
text = ''
|
|
pick_prev = min(len(self.text), self.pick_previous_segments)
|
|
for seg in self.text[-pick_prev:]:
|
|
# discard everything before a 3 second pause
|
|
if seg == '':
|
|
text = ''
|
|
else:
|
|
text += seg
|
|
wrapped = "".join(text + output)
|
|
return wrapped
|
|
|
|
def add_frames(self, frame_np):
|
|
try:
|
|
speech_prob = self.vad_model(torch.from_numpy(frame_np.copy()), self.RATE).item()
|
|
if speech_prob < self.vad_threshold:
|
|
return
|
|
|
|
except Exception as e:
|
|
logging.error(e)
|
|
return
|
|
|
|
if self.frames_np is not None and self.frames_np.shape[0] > 45*self.RATE:
|
|
self.frames_offset += 30.0
|
|
self.frames_np = self.frames_np[int(30*self.RATE):]
|
|
if self.frames_np is None:
|
|
self.frames_np = frame_np.copy()
|
|
else:
|
|
self.frames_np = np.concatenate((self.frames_np, frame_np), axis=0)
|
|
|
|
def speech_to_text(self):
|
|
"""
|
|
Process audio stream in an infinite loop.
|
|
"""
|
|
while True:
|
|
if self.exit:
|
|
logging.info("Exiting speech to text thread")
|
|
break
|
|
|
|
if self.frames_np is None:
|
|
continue
|
|
|
|
# clip audio if the current chunk exceeds 30 seconds, this basically implies that
|
|
# no valid segment for the last 30 seconds from whisper
|
|
if self.frames_np[int((self.timestamp_offset - self.frames_offset)*self.RATE):].shape[0] > 25 * self.RATE:
|
|
duration = self.frames_np.shape[0] / self.RATE
|
|
self.timestamp_offset = self.frames_offset + duration - 5
|
|
|
|
samples_take = max(0, (self.timestamp_offset - self.frames_offset)*self.RATE)
|
|
input_bytes = self.frames_np[int(samples_take):].copy()
|
|
duration = input_bytes.shape[0] / self.RATE
|
|
if duration<1.0:
|
|
continue
|
|
try:
|
|
input_sample = input_bytes.copy()
|
|
# set previous complete segment as initial prompt
|
|
if len(self.text) and self.text[-1] != '':
|
|
initial_prompt = self.text[-1]
|
|
else:
|
|
initial_prompt = None
|
|
|
|
# whisper transcribe with prompt
|
|
result = self.transcriber.transcribe(
|
|
input_sample,
|
|
initial_prompt=initial_prompt,
|
|
language=self.language,
|
|
task=self.task
|
|
)
|
|
|
|
if len(result):
|
|
self.t_start = None
|
|
last_segment = self.update_segments(result, duration)
|
|
if len(self.transcript) < self.send_last_n_segments:
|
|
segments = self.transcript
|
|
else:
|
|
segments = self.transcript[-self.send_last_n_segments:]
|
|
if last_segment is not None:
|
|
segments = segments + [last_segment]
|
|
|
|
try:
|
|
self.websocket.send(json.dumps(segments))
|
|
except Exception as e:
|
|
logging.info(f"[ERROR]: {e}")
|
|
else:
|
|
# show previous output if there is pause i.e. no output from whisper
|
|
segments = []
|
|
if self.t_start is None: self.t_start = time.time()
|
|
if time.time() - self.t_start < self.show_prev_out_thresh:
|
|
if len(self.transcript) < self.send_last_n_segments:
|
|
segments = self.transcript
|
|
else:
|
|
segments = self.transcript[-self.send_last_n_segments:]
|
|
|
|
# add a blank if there is no speech for 3 seconds
|
|
if len(self.text) and self.text[-1] != '':
|
|
if time.time() - self.t_start > self.add_pause_thresh:
|
|
self.text.append('')
|
|
|
|
try:
|
|
self.websocket.send(json.dumps(segments))
|
|
except Exception as e:
|
|
logging.info(f"[INFO]: {e}")
|
|
except Exception as e:
|
|
logging.info(f"[INFO]: {e}")
|
|
time.sleep(0.01)
|
|
|
|
def update_segments(self, segments, duration):
|
|
"""
|
|
Processes the segments from whisper. Appends all the segments to the list
|
|
except for the last segment assuming that it is incomplete.
|
|
|
|
Args:
|
|
segments(dict) : dictionary of segments as returned by whisper
|
|
duration(float): duration of the current chunk
|
|
|
|
Returns:
|
|
transcription for the current chunk
|
|
"""
|
|
offset = None
|
|
self.current_out = ''
|
|
last_segment = None
|
|
# process complete segments
|
|
if len(segments) > 1:
|
|
for i, s in enumerate(segments[:-1]):
|
|
text_ = s.text
|
|
self.text.append(text_)
|
|
start, end = self.timestamp_offset + s.start, self.timestamp_offset + min(duration, s.end)
|
|
self.transcript.append(
|
|
{
|
|
'start': start,
|
|
'end': end,
|
|
'text': text_
|
|
}
|
|
)
|
|
|
|
offset = min(duration, s.end)
|
|
|
|
self.current_out += segments[-1].text
|
|
last_segment = {
|
|
'start': self.timestamp_offset + segments[-1].start,
|
|
'end': self.timestamp_offset + min(duration, segments[-1].end),
|
|
'text': self.current_out
|
|
}
|
|
|
|
# if same incomplete segment is seen multiple times then update the offset
|
|
# and append the segment to the list
|
|
if self.current_out.strip() == self.prev_out.strip() and self.current_out != '':
|
|
self.same_output_threshold += 1
|
|
else:
|
|
self.same_output_threshold = 0
|
|
|
|
if self.same_output_threshold > 5:
|
|
if not len(self.text) or self.text[-1].strip().lower()!=self.current_out.strip().lower():
|
|
self.text.append(self.current_out)
|
|
self.transcript.append(
|
|
{
|
|
'start': self.timestamp_offset,
|
|
'end': self.timestamp_offset + duration,
|
|
'text': self.current_out
|
|
}
|
|
)
|
|
self.current_out = ''
|
|
offset = duration
|
|
self.same_output_threshold = 0
|
|
last_segment = None
|
|
else:
|
|
self.prev_out = self.current_out
|
|
|
|
# update offset
|
|
if offset is not None:
|
|
self.timestamp_offset += offset
|
|
|
|
return last_segment
|
|
|
|
def cleanup(self):
|
|
logging.info("Cleaning up.")
|
|
self.exit = True
|
|
self.transcriber.destroy()
|
|
|
|
|
|
if __name__ == "__main__":
|
|
with serve(recv_audio, "0.0.0.0", 9090) as server:
|
|
server.serve_forever() |