Voice activity detection
Voice activity detection (VAD), also known as speech activity detection or speech detection, is a technique used in speech processing in which the presence or absence of human speech is detected. The main uses of VAD are in speech coding and speech recognition. It can facilitate speech processing, and can also be used to deactivate some processes during non-speech section of an audio session: it can avoid unnecessary coding/transmission of silence packets in Voice over Internet Protocol applications, saving on computation and on network bandwidth.
VAD is an important enabling technology for a variety of speech-based applications. Therefore various VAD algorithms have been developed that provide varying features and compromises between latency, sensitivity, accuracy and computational cost. Some VAD algorithms also provide further analysis, for example whether the speech is voiced, unvoiced or sustained. Voice activity detection is usually language independent.
Noise suppression
Noise suppression aims to improve speech quality by using various algorithms. The objective of enhancement is improvement in intelligibility and/or overall perceptual quality of degraded speech signal using audio signal processing techniques.
Enhancing of speech degraded by noise, or noise reduction, is the most important field of noise suppression, and used for many applications such as mobile phones, VoIP, teleconferencing systems, speech recognition, and hearing aids.
Feedback cancelation
Adaptive feedback cancellation is a common method of cancelling audio feedback in a variety of electro-acoustic systems such as digital hearing aids. The time varying acoustic feedback leakage paths can only be eliminated with adaptive feedback cancellation. When an electro-acoustic system with an adaptive feedback canceller is presented with a correlated input signal, a recurrent distortion artifact, entrainment is generated. There is a difference between the system identification and feedback cancellation.
Adaptive feedback cancellation has its application in echo cancellation. The error between the desired and the actual output is taken and given as feedback to the adaptive processor for adjusting its coefficients to minimize the error.
In hearing aids, feedback arises when a part of the receiver (loudspeaker) signal is captured by the hearing aid microphone(s), gets amplified in the device and starts to loop around through the system. When feedback occurs, it results in a disturbingly loud tonal signal. Feedback is more likely to occur when the hearing aid volume is increased, when the hearing aid fitting is not in its proper position or when the hearing aid is brought close to a reflecting surface (e.g. when using a mobile phone). Adaptive feedback cancellation algorithms are techniques that estimate the transmission path between loudspeaker and microphone(s). This estimate is then used to implement a neutralizing electronic feedback path that suppresses the tonal feedback signal.