Updated: Jul 27, 2023
Solution Kit BUILD YOUR OWN VOICE TO TEXT CONVERTER
DESCRIPTION :-
Voice-to-Text AI, also known as Automatic Speech Recognition (ASR) or Speech-to-Text (STT) technology, is a form of artificial intelligence that converts spoken language into written text. This innovative technology allows computers and devices to understand and transcribe human speech, enabling users to interact with machines using their voice.
Voice-to-Text AI systems work by employing advanced machine learning algorithms, often based on deep learning models like recurrent neural networks (RNNs) or transformer architectures. During the training phase, these models are fed vast amounts of audio data paired with their corresponding transcriptions to learn the patterns and nuances of human speech.
This technology finds applications in a wide range of fields, including:-
1.Communication: Enabling voice commands in smartphones, virtual assistants (e.g., Siri, Alexa, Google Assistant), and smart home devices.
2.Transcription: Automatically transcribing meetings, interviews, lectures, and other spoken content, saving time and effort.
3.Accessibility: Assisting individuals with hearing impairments by providing real-time captions for live events or conversations.
rasaby RasaHQ
16550 Version:3.6.0💬 Open source machine learning framework to automate text- and voice-based conversations: NLU, dialogue management, connect to Slack, Facebook, and more - Create chatbots and voice assistants
rasaby RasaHQ
Python 16550 Version:3.6.0 License: Permissive (Apache-2.0)
chatgpt-on-wechatby zhayujie
13531 Version:1.3.1Wechat robot based on ChatGPT, which using OpenAI api and itchat library. Use ChatGPT to build a WeChat chat robot, based on GPT3.5/4.0 API, support personal WeChat, public account, enterprise WeChat deployment, can process text, voice and pictures, access Operating system and internet.
chatgpt-on-wechatby zhayujie
Python 13531 Version:1.3.1 License: Permissive (MIT)
code:-
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{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Speak something...\n",
"You said: hey bro\n"
]
}
],
"source": [
"import speech_recognition as sr\n",
"\n",
"def convert_voice_to_text():\n",
" # Initialize the recognizer\n",
" recognizer = sr.Recognizer()\n",
"\n",
" # Use the default microphone as the audio source\n",
" with sr.Microphone() as source:\n",
" print(\"Speak something...\")\n",
" recognizer.adjust_for_ambient_noise(source) # Adjust for background noise\n",
" audio = recognizer.listen(source) # Listen to the user's input\n",
"\n",
" try:\n",
" # Recognize the speech using Google Web Speech API\n",
" text = recognizer.recognize_google(audio)\n",
" print(\"You said:\", text)\n",
" except sr.UnknownValueError:\n",
" print(\"Sorry, I couldn't understand what you said.\")\n",
" except sr.RequestError as e:\n",
" print(\"Error occurred while making the request; {0}\".format(e))\n",
"\n",
"if __name__ == \"__main__\":\n",
" convert_voice_to_text()\n"
]
}
],
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