Speech recognition technology is the engine behind converting spoken language into written text. It's used in voice-controlled systems, transcription services, and voice assistants. This technology transforms audio input into machine-readable data, making voice interactions possible.
Speech recognition technology is the engine behind converting spoken language into written text. It's used in voice-controlled systems, transcription services, and voice assistants. This technology transforms audio input into machine-readable data, making voice interactions possible.
Neural networks are a fundamental component of deep learning. These complex mathematical models mimic the structure of the human brain and enable machines to learn patterns and make predictions. Deep learning models, such as those used in ChatGPT, rely on neural networks to perform complex tasks.
Audio signal processing involves analyzing, enhancing, and manipulating audio data. This technology is used for music recognition, sound enhancement, and noise reduction. It plays a crucial role in improving audio quality in various applications, from music streaming to conference calls.
Image processing encompasses a range of techniques for manipulating and analyzing images, while video processing involves tasks like video compression, object tracking, and video summarization. These technologies are vital for improving image and video quality and extracting meaningful information from visual data.
APIs (Application Programming Interfaces) are the connectors that enable seamless integration of these technologies into various applications and systems. They facilitate the communication between software components, making it easier to incorporate NLP, computer vision, speech recognition, and other AI capabilities into your solutions.
