Computer Audition teaches machines to interpret audio data. This covers all sound-related tasks, such as music recommendation, speech recognition, or environmental sound analysis.


Let’s say your computer is like your pet dog. You know how your dog can listen and understand when you call it, or how it can identify different noises, like the sound of a fire truck or a cat? Computer Audition is like teaching your computer to do those things, but with sounds and music!

In-depth explanation

Computer Audition (CA) is a subfield of artificial intelligence that focuses on interpreting audio data. It involves teaching machines to understand, process, and react to auditory signals in a manner akin to human audition. Advances in computer audition have been enabled by developments in machine learning and signal processing techniques.

The field extends to various applications. In speech recognition systems, CA is used to parse spoken language into written text. This is crucial for automated transcription services, voice assistants like Siri or Alexa, and many other applications where spoken commands are used to control systems.

Another application is music information retrieval, where CA is used to identify songs, classify genres, or recommend music based on user preferences. This is the sort of technology behind services like Shazam or Spotify’s Discover Weekly.

Sound event detection is another exciting area of exploration - identifying specific sounds within an audio stream, like car horns, gunshots, or birdsong. This has practical applications in security systems, wildlife monitoring, and urban planning.

In each of these cases, techniques such as Fourier Transformations, Spectrograms, and Wavelets are used to extract features from audio signals. These features can then be fed into machine learning models like Neural Networks or Support Vector Machines to perform tasks like classification, detection, or recommendation.

The field continues to evolve, with deep learning methodologies and advanced signal processing algorithms helping to improve the sophistication of computer audition systems.

Speech Recognition, Music Information Retrieval, Sound Event Detection, Machine Learning (ML),, Artificial Intelligence, Signal Processing, Fourier Transformation, Spectrogram, Wavelet, Neural Networks, Support Vector Machines.