Files
conjurer/voice_recognition.py
T
2024-09-20 17:19:17 +02:00

228 lines
9.3 KiB
Python

import logging
import wave
import asyncio
import assemblyai as aai
import discord
from discord.ext import commands, voice_recv, tasks
from discord.opus import Decoder as OpusDecoder
import time
# Replace with your API key
aai.settings.api_key = "aa9962f0088a449a9c4ab2361e96cc08"
discord.opus._load_default()
CHANNELS = OpusDecoder.CHANNELS
SAMPLE_WIDTH = OpusDecoder.SAMPLE_SIZE // OpusDecoder.CHANNELS
SAMPLING_RATE = OpusDecoder.SAMPLING_RATE
#rotate file after there is 0.5s between last received pcm for user.
#delete messsages after user disconnect
logger = logging.getLogger("discord")
location = "/home/pi/Conjurer/transcripts/"
class CommunicationObject:
def __init__(self, msg_type, user, data):
self.type = msg_type
self.user = user
self.data = data
class WaveWriter:
def __init__(self, user_id, queue):
self.queue = queue
logger.info("Wavewriter queue id: %s",id(self.queue))
self.user = user_id
self.username = str(user_id.id)
logger.info("Creating Wavewriter %s", self.username)
logger.info(user_id)
self.present_file_id = 0
self.file_name_past = None
self.file_name_present = location + self.username + "_" + str(self.present_file_id) + ".mp3"
self.transcript_file_present : wave.Wave_write = wave.open(
self.file_name_present, "wb"
)
self.transcript_file_present.setnchannels(CHANNELS)
self.transcript_file_present.setsampwidth(SAMPLE_WIDTH)
self.transcript_file_present.setframerate(SAMPLING_RATE)
self.file_name_future = location + self.username + "_" + str(self.present_file_id + 1) + ".mp3"
self.transcript_file_future : wave.Wave_write = wave.open(
self.file_name_future, "wb"
)
self.transcript_file_future.setnchannels(CHANNELS)
self.transcript_file_future.setsampwidth(SAMPLE_WIDTH)
self.transcript_file_future.setframerate(SAMPLING_RATE)
async def rotate(self):
self.transcript_file_present.close()
self.file_name_past = self.file_name_present
if self.present_file_id > 10:
self.present_file_id = 0
else:
self.present_file_id += 1
self.file_name_present = self.file_name_future
self.transcript_file_present = self.transcript_file_future
self.file_name_future = location + self.username + "_" + str(self.present_file_id + 1) + ".mp3"
self.transcript_file_future : wave.Wave_write = wave.open(
self.file_name_future, "wb"
)
self.transcript_file_future.setnchannels(CHANNELS)
self.transcript_file_future.setsampwidth(SAMPLE_WIDTH)
self.transcript_file_future.setframerate(SAMPLING_RATE)
operation = CommunicationObject(msg_type="send_file",user=self.user,data=[self.file_name_present])
logger.info("Item added to queue %s %s", self.queue, operation)
await self.queue.put(operation)
def writeframes(self, pcmdata):
self.transcript_file_present.writeframes(pcmdata)
def cleanup(self):
logger.info("Cleanup for user %s", self.username)
self.transcript_file_present.close()
self.transcript_file_future.close()
class SRBuffer(voice_recv.AudioSink):
"""Endpoint AudioSink that generates a wav file.
Best used in conjunction with a silence generating sink. (TBD)
"""
# on member join dodajemytypa do listy
# on member disconnect - dropujemy go
def __init__(self, queue):
super().__init__()
self.queue = queue
self.wavewriter = {}
def on_user_connect(self, username):
self.wavewriter[str(username.id)] = [WaveWriter(username, self.queue), time.time_ns(), time.time_ns(), False, False]
def on_user_disconnect(self,username):
self.wavewriter[str(username.id)].cleanup()
self.wavewriter.pop(str(username.id))
def wants_opus(self) -> bool:
return False
def write(self, user, data) -> None:
#logger.info("DAta write")
if user:
self.wavewriter[str(user.id)][0].writeframes(data.pcm)
self.wavewriter[str(user.id)][1] = time.time_ns() #time from last write
self.wavewriter[str(user.id)][3] = True #data written in last iter
self.wavewriter[str(user.id)][4] = True #data in buff
time.sleep(0.001)
def cleanup(self) -> None:
try:
logger.info("Cleanup for SRBuffer")
for item in self.wavewriter.values():
item[0].cleanup()
except Exception:
logger.warning("WaveSink got error closing file on cleanup", exc_info=True)
class Transcriber(commands.Cog):
def __init__(self, bot):
self.bot = bot
self.threads = []
self.comm_queue = asyncio.Queue()
self.wsink = SRBuffer(self.comm_queue)
self.worker = None
@commands.hybrid_command(name="transcribe")
async def test(self, ctx):
logger.info("Attempt transcribe")
vc = None
if self.bot.voice_clients:
if isinstance(self.bot.voice_clients[0], voice_recv.VoiceRecvClient):
logger.info("Already transcribing")
else:
logger.info("Already connected with other client")
logger.info(self.bot.voice_clients)
else:
logger.info("Connected")
vc = await ctx.author.voice.channel.connect(cls=voice_recv.VoiceRecvClient)
logger.info(self.bot.voice_clients)
self.check_data.start()
logger.info("Start worker!~!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!")
self.worker = asyncio.create_task(self.transcribe_output_queue())
vc.listen(self.wsink)
@tasks.loop(seconds=0.5)
async def check_data(self):
for item in self.wsink.wavewriter.values():
logger.info("Item %s", item)
if not item[3]:
timediff_rotation = time.time_ns() - item[2]
timediff_write = time.time_ns() -item[1]
if timediff_rotation > 3000149433 and timediff_write > 500014943 and item[4]:
logger.info("File rotation time since last write %s", timediff_write/1e9)
logger.info("File rotation time since last rotation %s", timediff_rotation/1e9)
item[2] = time.time_ns()
item[4] = False
await item[0].rotate()
item[3] = False
@commands.Cog.listener()
async def on_voice_state_update(self, user, before, after):
if user == self.bot.user:
logger.info("Ignoring self")
return
if before.channel is None:
logger.info("User %s connected to channel %s", user, after.channel.name)
self.wsink.on_user_connect(user)
elif after.channel is None:
logger.info("User %s disconnected from channel %s", user, before.channel.name)
operation = CommunicationObject(msg_type="user_cleanup", user=user, data=None)
logger.info("Item added to queue %s %s", self.comm_queue, operation)
await self.comm_queue.put(operation)
else:
logger.info("User VC status changed %s", user.id)
logger.info("Before %s", before)
logger.info("After %s", after)
@commands.command(name="stop_transcribe")
async def stop(self, ctx):
self.check_data.stop()
stop_token = CommunicationObject("STOP",None,None)
logger.info("Item added to queue %s %s", self.comm_queue, stop_token)
await self.comm_queue.put(stop_token)
await ctx.voice_client.disconnect()
async def transcribe_output_queue(self):
logger.info("Transcript worker start")
config = aai.TranscriptionConfig(speaker_labels=True, language_code="pl")
transcriber = aai.Transcriber()
logger.info("Transcriber queue id: %s",id(self.comm_queue))
while True:
logger.info("waiting for tasks")
item = await self.comm_queue.get()
logger.info("Got %s", item)
if item.type == "STOP":
logger.info("Queue ended")
break
elif item.type == "send_file":
transcript = ""
for iter in item.data:
transcript = transcriber.transcribe(iter, config=config)
for utterance in transcript.utterances:
logger.info("%s : %s", item.user, utterance.text)
elif item.type == "user_cleanup":
logger.info("User %s disconnected - cleanup action")
else:
logger.warn("Something went wrong with object %s", item)
logger.info("End transcript worker")
async def setup(bot):
logger = logging.getLogger("discord")
await bot.add_cog(Transcriber(bot))
logger.info("Loading voice transcribed module done")
# 1. zapisuj kwestie człowieka do pliku w którym będzie można stwierdzić kto co powiedział (callback z basicaudio + write z wavesinka). Zamykaj plik i wysyłaj do transkrypcji w momencie ciszy dłuższej niż 0.5s. Jeśli człowiek nadaje cały czas dawaj sygnał że nie można go transkrybować - i wyłaczaj zapis.
# 2. Transkrypcja to abstrakt - w zależności od tego która metoda jest włączona wysyła do odpowiedniego silnika, silniki offline odpalam na activcomie. Zaczynamy od assemblyai bo najlepiej wspiera polski. Potem zobaczymy co dalej.