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It is well known that the LSP coe cient which represents the speech spectrum envelope as one of the linear prediction coe cients, shows a good performance of spectral interpolation along the time axis, but it is also known that the duration of interpolation is limited up to 20 30 ms. This limitation makes it di cult to reduce the bit rate in very low bit rate speech coding. To resolve this problem, recurrent neural networks (RNN) were applied to interpolate LSP coe cients, and it was possible to increase the duration of interpolation to about 100 ms without so much degradation of the synthesized speech quality.

An Application of Recurrent Neural Networks to Low Bit Rate Speech Coding