A Review on Sign Language to Text and Speech Conversion

Sign language functions as an important type of communication for people with hearing and speech impairments. .

However, the broad lack of knowledge in sign language in the general population indicates an important communication

barrier. This review paper examines the progress of the sign language recognition system, converting gestures into text and

language, facilitating actual communication. Although traditional methods are based on sensor-based or computer vision

techniques, the latest developments in deep learning, particularly in frameworks such as Neuron Networks (CNNS) and

MediaPipe have significantly improved identification accuracy. This article examines various approaches and highlights their

advantages, limitations, and their practical applicability. Furthermore, you can use issues such as data. We will explain the

flashiness of the model and the actual time processing limits. By reviewing existing research and technological advances, this

study aims to provide insight into the optimization of speech translation systems for broader accessibility and practical delivery.

Vision, Signal Language Translation, Text-to-Speech (TTS) Synthesis, Google Text-to-Speech (GTTS), Natural Language

Processing (NLP).