Search results
Results from the WOW.Com Content Network
Speech processing is the study of speech signals and the processing methods of signals. The signals are usually processed in a digital representation, so speech processing can be regarded as a special case of digital signal processing , applied to speech signals .
A speech sound is influenced by the ones that precede and the ones that follow. This influence can even be exerted at a distance of two or more segments (and across syllable- and word-boundaries). [5] Because the speech signal is not linear, there is a problem of segmentation. It is difficult to delimit a stretch of speech signal as belonging ...
Speech coding is an application of data compression to digital audio signals containing speech.Speech coding uses speech-specific parameter estimation using audio signal processing techniques to model the speech signal, combined with generic data compression algorithms to represent the resulting modeled parameters in a compact bitstream.
In speech communication, intelligibility is a measure of how comprehensible speech is in given conditions. Intelligibility is affected by the level (loud but not too loud) and quality of the speech signal, the type and level of background noise, reverberation (some reflections but not too many), and, for speech over communication devices, the properties of the communication system.
Linear predictive coding (LPC) is a method used mostly in audio signal processing and speech processing for representing the spectral envelope of a digital signal of speech in compressed form, using the information of a linear predictive model. [1] [2] LPC is the most widely used method in speech coding and speech synthesis.
Speech and music quality for signals subjected to noise and clipping distortion have also been modeled using the coherence [257] or using the coherence averaged across short signal segments. [258] Changes in the signal envelope can be measured using several different procedures.
Speech recognition is an interdisciplinary subfield of computer science and computational linguistics that develops methodologies and technologies that enable the recognition and translation of spoken language into text by computers. It is also known as automatic speech recognition (ASR), computer speech recognition or speech-to-text (STT).
Modern speech recognition systems use both an acoustic model and a language model to represent the statistical properties of speech. The acoustic model models the relationship between the audio signal and the phonetic units in the language. The language model is responsible for modeling the word sequences in the language.