Intelligible semantic level speech compression algorithm by preserving emotional content
A. Firos, Utpal Bhattacharjee · 2017
Speech encoding refers to compression for transmission or storage, possibly to an unintelligible state, with decompression used prior to playback. This paper attempts to formulate the semantic level compression technique on speech signals by preserving its prosodic features. LPC analysis will be done to identify the feature of the input speech. GMM will be used to preserve the emotional content while encoding. ANN will be utilized to identify the best features for encoding. Using such semantic based coding will highly reduce the computational overhead in speech coders.