A speech recognition apparatus (2000) includes a first model (10) and a second model (20). The first model (10) is learned by training data with an audio frame as input data, and with, as correct answer data, compressed character string data acquired by encoding character string data represented by the audio frame. The second model (20) is a learned decoder (44) acquired by learning an autoencoder (40) being constituted of an encoder (42) converting input character string data into compressed character string data, and the decoder (44) converting, into character string data, the compressed character string data output from the encoder. The speech recognition apparatus (2000) inputs an audio frame to the first model (10), inputs, to the second model (20), compressed character string data output from the first model (10), and thereby generates character string data corresponding to the audio frame.

A coding method and a decoding method are provided which can use in combination a predictive coding and decoding method which is a coding and decoding method that can accurately express coefficients which are convertible into linear prediction coefficients with a small code amount and a coding and decoding method that can obtain correctly, by decoding, coefficients which are convertible into linear prediction coefficients of the present frame if a linear prediction coefficient code of the present frame is correctly input to a decoding device. A coding device includes: a predictive coding unit that obtains a first code by coding a differential vector formed of differentials between a vector of coefficients which are convertible into linear prediction coefficients of more than one order of the present frame and a prediction vector containing at least a predicted vector from a past frame, and obtains a quantization differential vector corresponding to the first code; and a non-predictive coding unit that generates a second code by coding a correction vector which is formed of differentials between the vector of the coefficients which are convertible into the linear prediction coefficients of more than one order of the present frame and the quantization differential vector or formed of some of elements of the differentials.

An information encoder for encoding an information signal includes: a converter for converting the linear prediction coefficients of the predictive polynomial A(z) to frequency values f.sub.1 . . . f.sub.n of a spectral frequency representation of the predictive polynomial A(z), wherein the converter is configured to determine the frequency values f.sub.1 . . . f.sub.n by analyzing a pair of polynomials P(z) and Q(z) being defined as $P\left(z\right)=A\left(z\right)+z^{-m-l}A\left(z^{-1}\right)\mathrm{and}$$Q\left(z\right)=A\left(z\right)-z^{-m-l}A\left(z^{-1}\right),$
wherein m is

A high quality speech is reproduced with a small data amount in speech coding and decoding for performing compression coding and decoding of a speech signal to a digital signal. In speech coding method according to a code-excited linear prediction (CELP) speech coding, a noise level of a speech in a concerning coding period is evaluated by using a code or coding result of at least one of spectrum information, power information, and pitch information, and various excitation codebooks are used based on an evaluation result.

Methods, an encoder and a decoder are configured for transition between frames with different internal sampling rates. Linear predictive (LP) filter parameters are converted from a sampling rate S1 to a sampling rate S2. A power spectrum of a LP synthesis filter is computed, at the sampling rate S1, using the LP filter parameters. The power spectrum of the LP synthesis filter is modified to convert it from the sampling rate S1 to the sampling rate S2. The modified power spectrum of the LP synthesis filter is inverse transformed to determine autocorrelations of the LP synthesis filter at the sampling rate S2. The autocorrelations are used to compute the LP filter parameters at the sampling rate S2.

An encoding method includes dividing a to-be-encoded time-domain signal into a low band signal and a high band signal, performing encoding on the low band signal to obtain a low frequency encoding parameter, performing encoding on the high band signal to obtain a high frequency encoding parameter, obtaining a synthesized high band signal, performing short-time post-filtering processing on the synthesized high band signal to obtain a short-time filtering signal, and calculating a high frequency gain based on the high band signal and the short-time filtering signal.

An apparatus for decoding an encoded audio signal to obtain a reconstructed audio signal includes a receiving interface for receiving one or more frames comprising information on a plurality of audio signal samples of an audio signal spectrum of the encoded audio signal, and a processor for generating the reconstructed audio signal. The processor is configured to generate the reconstructed audio signal by fading a modified spectrum to a target spectrum, if a current frame is not received by the receiving interface or if the current frame is received by the receiving interface but is corrupted, wherein the modified spectrum includes a plurality of modified signal samples, wherein, for each of the modified signal samples of the modified spectrum, an absolute value of the modified signal sample is equal to an absolute value of one of the audio signal samples of the audio signal spectrum.

An arrangement is described for speech signal processing. An input microphone signal is received that includes a speech signal component and a noise component. The microphone signal is transformed into a frequency domain set of short-term spectra signals. Then speech formant components within the spectra signals are estimated based on detecting regions of high energy density in the spectra signals. One or more dynamically adjusted gain factors are applied to the spectra signals to enhance the speech formant components.

A coding method and a decoding method are provided which can use in combination a predictive coding and decoding method which is a coding and decoding method that can accurately express coefficients which are convertible into linear prediction coefficients with a small code amount and a coding and decoding method that can obtain correctly, by decoding, coefficients which are convertible into linear prediction coefficients of the present frame if a linear prediction coefficient code of the present frame is correctly input to a decoding device. A coding device includes: a predictive coding unit that obtains a first code by coding a differential vector formed of differentials between a vector of coefficients which are convertible into linear prediction coefficients of more than one order of the present frame and a prediction vector containing at least a predicted vector from a past frame, and obtains a quantization differential vector corresponding to the first code; and a non-predictive coding unit that generates a second code by coding a correction vector which is formed of differentials between the vector of the coefficients which are convertible into the linear prediction coefficients of more than one order of the present frame and the quantization differential vector or formed of some of elements of the differentials.

A frame loss compensation processing method and apparatus is presented, where the method includes, when a i.sup.th frame is a lost frame, estimating a spectrum frequency parameter, a pitch period, and a gain of the i.sup.th frame according to at least one of an inter-frame relationship between first N frames of the i.sup.th frame or an intra-frame relationship between first N frames of the i.sup.th frame. A parameter of the i.sup.th frame is determined using the signal correlation between the first N frames, the signal energy stability between the first N frames, intra-frame signal correlation of each frame, and intra-frame signal energy stability of each frame.