def transcribe(file):
prepareFile = file.split("-")
if (prepareFile[2] in ['mp3', 'wav', 'm4a']):
file_url = "https://cdn.sanity.io/files/{}/{}/{}.{}".format(PROJECT_ID, DATASET, prepareFile[1], prepareFile[2])
aai = assemblyai.Client(token=ASSEMBLY_TOKEN)
transcript = aai.transcribe(audio_url=file_url)
while transcript.status != 'completed':
print(transcript.status)
transcript = transcript.get()
text = transcript.text
print(text)
mutations = {
"mutations": [{
"patch": {
"id": file,
"set": {
"transcription": {
"text": text,
"service": "assemblyai"
}
}
}
}]
}
print("Sending transript of {} to Sanity".format(file))
r = requests.post(mutations_api, data=json.dumps(mutations), headers=auth_header)
if (r.status_code == 200 and SLACK_WEBHOOK_URL):
payload = { "text": "File {} was transcribed successfully".format(file) }
requests.post(SLACK_WEBHOOK_URL, data=json.dumps(payload))
else:
payload = { "text": "An error happened when transcribing {}: {}".format(file, r.message) }
requests.post(SLACK_WEBHOOK_URL, data=json.dumps(payload))
"""
For stereo audio with two speakers on separate channels, you can leverage
enhanced accuracy and formatting by setting speak_count to 2.
"""
import assemblyai
aai = assemblyai.Client()
model = aai.transcribe('example.wav', speaker_count=2)
from translate import Translator
import assemblyai
import time
from gtts import gTTS
import os
#key for API
aai = assemblyai.Client(token='bbc8f48274684b24944a9ed0ec6056b7')
#Temp Text file
transcript = aai.transcribe(filename='example.txt')
#Audio File to be translated
transcript = aai.transcribe(filename='Mum.mp3')
#takes audio from mp3 file and converts to text
while transcript.status != 'completed':
transcript = transcript.get()
#adds text to text variable
text = transcript.text
#prints the text
print("English: " + text)
print("\n")
#To Translate text from english to other language
def tran(toTran, lang):
translator = Translator(From_lang="autodetect", to_lang=lang)
translation = translator.translate(toTran)
print(lang + ": " + translation)
import assemblyai
aai = assemblyai.Client(token=' 11fc9ccf99d040b5a831216a17556e4e')
transcript = aai.transcribe(filename='/home/adhoc/non-coder/aud.wav')
while transcript.status != 'completed':
transcript = transcript.get()
text = transcript.text
import subprocess
import assemblyai as aai
import json
import sys
import time
import requests
import summarize
token = 'cc0738780ad94cd29c92750529eb5f5a'
ai = aai.Client(token=token)
def saveAudio(username, video):
vpath = "Database/Users/" + username + "/Videos/Video " + str(video)
command = 'ffmpeg -i "Database/Users/' + username + '/Videos/Video ' + str(
video
) + '/video.mp4" -vn -ab 160k -ac 1 -ar 44100 -vn "Database/Users/' + username + '/Videos/Video ' + str(
video) + '/audio.mp3"'
subprocess.call(command, shell=True)
with open(vpath + "/videodetails.json", "r") as readfile:
vjson = json.load(readfile)
username = vjson['username']
videono = vjson['videono']
title = vjson['title']
description = vjson['description']
keywords = vjson['keywords']
savestatus = vjson['savestatus']
audiosavedstatus = vjson['audiosavedstatus']
assemblystatus = vjson['assemblystatus']
transcriptstatus = vjson['transcriptstatus']
import json
import requests
import assemblyai
url = 'https://api.assemblyai.com/transcript'
token = None
headers = {'authorization': token}
audio_file = 'f.mp3'
audio_file = 'https://avilpage.com/media/audio/blob_ZzyEsGT'
data = json.dumps({'audio_src_url': audio_file})
r = requests.post(url, data=data, headers=headers)
aai = assemblyai.Client(token=token)
audio_file = 'audio/blob_05Qf5MO'
transcript = aai.transcribe(filename=audio_file)
while transcript.status != 'completed':
transcript = transcript.get()
text = transcript.text
print(text)
import sys
import assemblyai
import TextAnalysis as ta
print("Type of cmd line arguments are ", type(sys.argv))
fileName = sys.argv[1]
try:
aai = assemblyai.Client(token='Your Assembly AI token ID')
transcript = aai.transcribe(filename=fileName)
while transcript.status != 'completed':
transcript = transcript.get()
text = transcript.text
print(text)
text = transcript.text
print(text)
ta.Analyze(text)
except ConnectionError:
print("Error occured, Please check your internet connection.")