A Python ML project that converts spoken language into text using speech recognition, and transforms text into spoken words using speech synthesis. Harness the power of machine learning to effortlessly transcribe and vocalize audio inputs. Enhance accessibility and communication in a streamlined, efficient manner.
The project utilizes the speech_recognition library to capture audio input from a microphone. By employing techniques such as ambient noise adjustment and Google's speech recognition API, the program accurately converts spoken words into text. This functionality opens up a wide range of applications, from automated transcription services to voice-controlled interfaces.
On the other hand, the project employs the pyttsx3 library for text-to-speech conversion. By utilizing the text-to-speech engine, the program vocalizes the processed text, enabling users to listen to the synthesized output.
This project aims to enhance accessibility, improve communication, and streamline various tasks. It can be integrated into applications, devices, or systems where speech recognition and synthesis are crucial. By providing a robust and user-friendly solution, "Speech2Text & SpeakIt" empowers users to interact with technology through voice commands, facilitates efficient transcription services, and enables individuals with visual impairments to consume written content with ease.
With its ability to seamlessly convert speech to text and text to speech, "Speech2Text & SpeakIt" opens up new possibilities for efficient communication and accessibility in diverse domains such as voice assistants, transcription services, language learning tools, and more.