I am trying to integrate azure text to speech with streamlit.
import azure.cognitiveservices.speech as speechsdk
import streamlit as st
st.title("Let's learn Math!")
def recognize_from_microphone():
speech_config = speechsdk.SpeechConfig(subscription="743ae1f5555f49f9a5de4457d4e91b2d", region="australiaeast")
speech_config.speech_recognition_language="en-US"
#To recognize speech from an audio file, use `filename` instead of `use_default_microphone`:
#audio_config = speechsdk.audio.AudioConfig(filename="YourAudioFile.wav")
audio_config = speechsdk.audio.AudioConfig(use_default_microphone=True)
speech_recognizer = speechsdk.SpeechRecognizer(speech_config=speech_config, audio_config=audio_config)
st.text("Speak into your microphone.")
speech_recognition_result = speech_recognizer.recognize_once_async().get()
if speech_recognition_result.reason == speechsdk.ResultReason.RecognizedSpeech:
st.text("Recognized: {}".format(speech_recognition_result.text))
elif speech_recognition_result.reason == speechsdk.ResultReason.NoMatch:
st.text("No speech could be recognized: {}".format(speech_recognition_result.no_match_details))
elif speech_recognition_result.reason == speechsdk.ResultReason.Canceled:
cancellation_details = speech_recognition_result.cancellation_details
st.text("Speech Recognition canceled: {}".format(cancellation_details.reason))
if cancellation_details.reason == speechsdk.CancellationReason.Error:
st.text("Error details: {}".format(cancellation_details.error_details))
st.text("Did you set the speech resource key and region values?")
text = st.text_input("Enter text", value="Hi", max_chars=5)
def audio_output(text):
speech_config = speechsdk.SpeechConfig(subscription="743ae1f5555f49f9a5de4457d4e91b2d", region="australiaeast")
audio_config = speechsdk.audio.AudioOutputConfig(use_default_speaker=True)
# The language of the voice that speaks.
speech_config.speech_synthesis_voice_name='en-US-JennyNeural'
speech_synthesizer = speechsdk.SpeechSynthesizer(speech_config=speech_config, audio_config=audio_config)
# Get text from the console and synthesize to the default speaker.
st.write("Enter some text that you want to speak >")
speech_synthesis_result = speech_synthesizer.speak_text_async(text).get()
if speech_synthesis_result.reason == speechsdk.ResultReason.SynthesizingAudioCompleted:
st.write("Speech synthesized for text [{}]".format(text))
elif speech_synthesis_result.reason == speechsdk.ResultReason.Canceled:
cancellation_details = speech_synthesis_result.cancellation_details
st.write("Speech synthesis canceled: {}".format(cancellation_details.reason))
if cancellation_details.reason == speechsdk.CancellationReason.Error:
if cancellation_details.error_details:
st.write("Error details: {}".format(cancellation_details.error_details))
st.write("Did you set the speech resource key and region values?")
recognize_from_microphone()
audio_output(text)
This is my code, but streamlit is not loading the functions at all. Is there any fix? I am new to streamlit and azure.
You declared the functions but didn't called them.
Related
I have this simple code: notify me with audio and notification tasks every time I press Alt+Shift to switch in one of the four (Italia, Hebrew, English, and Spanish) keyboard layouts.
import keyboard
import time
import ctypes
import json
import plyer
import pyttsx3
def on_alt(event):
if keyboard.is_pressed('alt'):
time.sleep(0.5)
user32 = ctypes.WinDLL('user32', use_last_error=True)
curr_window = user32.GetForegroundWindow()
thread_id = user32.GetWindowThreadProcessId(curr_window, 0)
klid = user32.GetKeyboardLayout(thread_id)
lid = klid & (2**16 - 1)
key_list = list(lcid.keys())
val_list = list(lcid.values())
position = key_list.index(str(lid))
if(str(lid) == '1040'):
engine = pyttsx3.init()
engine.say("Italian")
engine.runAndWait()
elif(str(lid) == '1037'):
engine = pyttsx3.init()
engine.say("Hebrew")
engine.runAndWait()
elif(str(lid) == '2058'):
engine = pyttsx3.init()
engine.say("Spanish")
engine.runAndWait()
elif(str(lid) == '1033'):
engine = pyttsx3.init()
engine.say("English")
engine.runAndWait()
plyer.notification.notify(
title = "Language Keyboard Switch",
message = str(val_list[position]),
timeout = 0.1
)
lcid = {"1040": "it_IT",
"1033": "en_US",
"1037": "he_IL",
"2058": "es_MX",
}
keyboard.on_press_key('shift', on_alt)
time.sleep(1e6)
Running the script as it is, it works fine. But when I build EXEcutable in Windows 10 with pyinstaller it returns this error when I press Alt+Shift
It's weird that the same executable built in Windows 11 it works fine.
I want to change the voice of azure from python, with these characteristics
languageCode = 'es‑MX'
ssmlGender = 'FEMALE'
voicName = 'es‑MX‑DaliaNeural'
but i'm new to azure so i don't know how, this is my code:
import PyPDF2
import azure.cognitiveservices.speech as sdk
key = "fake key"
region = "fake region"
config = sdk.SpeechConfig(subscription=key, region=region)
synthesizer = sdk.SpeechSynthesizer(speech_config=config)
book = open("prueba.pdf", "rb")
reader = PyPDF2.PdfFileReader(book)
for num in range(0,reader.numPages):
text = reader.getPage(num).extractText()
result = synthesizer.speak_text_async(text).get()
Acording to the documentation https://learn.microsoft.com/en-us/azure/cognitive-services/speech-service/how-to-speech-synthesis?tabs=browserjs%2Cterminal&pivots=programming-language-python#select-synthesis-language-and-voice you should be able to do:
config.speech_synthesis_language = "es‑MX"
config.speech_synthesis_voice_name ="es-MX-DaliaNeural"
The list of voices is here https://learn.microsoft.com/en-us/azure/cognitive-services/speech-service/language-support?tabs=tts
I am learning to use pyttsx3 module.
I want to make a continuous speech without any pauses so I deleted all '.' and ',', but pauses are created in what I thought were random places. So dug deeper and figured that it makes a pause every 82 (+/-1 words).
Any idea how to fix it?
Here is my code:
import pyttsx3
with open('D:\D-Chilldom\QuickMovieRecap\Movie.txt', 'r') as f:
text = f.read()
text = text.replace('.', '')
text = text.replace(',', '')
# Initialize the TTS engine
engine = pyttsx3.init()
# Set the rate of speech (words per minute)
rate = 250
engine.setProperty('rate', rate)
# Set the volume of the voice
volume = 1
engine.setProperty('volume', volume)
# Set the voice to use
voice_id = "com.apple.speech.synthesis.voice.samantha"
engine.setProperty('voice', voice_id)
engine.save_to_file(text, 'D:/D-Chilldom/QuickMovieRecap/rec/zzzz.mp3')
engine.runAndWait()
As a personal project, I decided to create one of the reddit text-to-speech bot.
I pulled all the data from reddit with praw
import praw, random
def scrapeData(subredditName):
# Instantiate praw
reddit = praw.Reddit()
# Get subreddit
subreddit = reddit.subreddit(subredditName)
# Get a bunch of posts and convert them into a list
posts = list(subreddit.new(limit=100))
# Get random number
randomNumber = random.randint(0, 100)
# Store post's title and description in variables
postTitle = posts[randomNumber].title
postDesc = posts[randomNumber].selftext
return postTitle + " " + postDesc
Then, I converted it to speech stored in a .mp3 file with gTTS.
from google.cloud import texttospeech
def convertTextToSpeech(textString):
# Instantiate TTS
client = texttospeech.TextToSpeechClient().from_service_account_json("path/to/json")
# Set text input to be synthesized
synthesisInput = texttospeech.SynthesisInput(text=textString)
# Build the voice request
voice = texttospeech.VoiceSelectionParams(language_code = "en-us",
ssml_gender = texttospeech.SsmlVoiceGender.MALE)
# Select the type of audio file
audioConfig = texttospeech.AudioConfig(audio_encoding =
texttospeech.AudioEncoding.MP3)
# Perform the TTS request on the text input
response = client.synthesize_speech(input = synthesisInput, voice =
voice, audio_config= audioConfig)
# Convert from binary to mp3
with open("output.mp3", "wb") as out:
out.write(response.audio_content)
I've created an .mp4 with moviepy that has generic footage in the background with the audio synced over it,
from moviepy.editor import *
from moviepy.video.tools.subtitles import SubtitlesClip
# get vide and audio source files
clip = VideoFileClip("background.mp4").subclip(20,30)
audio = AudioFileClip("output.mp3").subclip(0, 10)
# Set audio and create final video
videoClip = clip.set_audio(audio)
videoClip.write_videofile("output.mp4")
but my issue is I can't find a way to have only the current word or sentence displayed on screen as a subtitle, rather than the entire post.
I have a wav conversation of 2 people(customer and tech support)
I have 3 separate functions that extract 1 voice, cut 10 seconds and transform it to embedding.
def get_customer_voice(file):
print('getting customer voice only')
wav = wf.read(file)
ch = wav[1].shape[1]#customer voice always in 1st track
sr = wav[0]
c1 = wav[1][:,1]
#print('c0 %i'%c0.size)
if ch==1:
exit()
vad = VoiceActivityDetection()
vad.process(c1)
voice_samples = vad.get_voice_samples()
#this is trouble - how to pass it without saving anywhere as wav?
wf.write('%s_customer.wav'%file,sr,voice_samples)
function below cuts 10 seconds of wav file from function above.
import sys
from pydub import AudioSegment
def get_customer_voice_10_seconds(file):
voice = AudioSegment.from_wav(file)
new_voice = voice[0:10000]
file = str(file) + '_10seconds.wav'
new_voice.export(file, format='wav')
if __name__ == '__main__':
if len(sys.argv) < 2:
print('give wav file to process!')
else:
print(sys.argv)
get_customer_voice_10_seconds(sys.argv[1])
how to pass it as wav or other format without saving it to some directory? It's to be used in rest api, i don't know where it will save that wav, so preferably it should be passed somehow.
I figured it out - the function below just works without saving, buffer etc.
It receives a wav file and edits it and just sends straight to the get math embedding function:
def get_customer_voice_and_cutting_10_seconds_embedding(file):
print('getting customer voice only')
wav = read(file)
ch = wav[1].shape[1]
sr = wav[0]
c1 = wav[1][:,1]
vad = VoiceActivityDetection()
vad.process(c1)
voice_samples = vad.get_voice_samples()
audio_segment = AudioSegment(voice_samples.tobytes(), frame_rate=sr,sample_width=voice_samples.dtype.itemsize, channels=1)
audio_segment = audio_segment[0:10000]
file = str(file) + '_10seconds.wav'
return get_embedding(file)
the key is tobytes() in Audio segment, it just assembles all them together in 1 track again