Abstract: The present disclosure relates to a decoding method, apparatus and computer-readable storage medium, which relates to the field of computer technology. The method of the present disclosure includes buffering one or more stream segments of a data stream which are received, wherein the data stream comprises an audio stream; parsing the one or more stream segments buffered until header information is obtained through the parsing; storing the header information; and decoding stream segments of the audio stream among various stream segments received according to the header information until the audio stream is completely decoded.

Abstract: A human-computer interaction method and apparatus. Said method may include: receiving information of at least one modality of a user (201); identifying, on the basis of the information of the at least one modality, intention information of the user and user emotional features corresponding to the intention information (202); determining, on the basis of the intention information, reply information to the user (203); selecting, on the basis of the user emotional features, character emotional features to be fed back to the user (204); and generating, on the basis of the character emotional features and the reply information, a broadcast video of an animated character corresponding to the character emotional features (205).

Abstract: Provided are a speech recognition method, a speech recognition apparatus, a computer readable storage medium, and an electronic device. The method comprises: obtaining a sample speech signal, decoding the sample speech signal, obtaining a decoding result, and extracting a first feature from the decoding result; extracting a target speech segment from the sample speech signal, obtaining a log magnitude spectrum of the target speech segment, and determining a second feature according to the log magnitude spectrum; combining the first feature and the second feature to obtain a third feature; training an untrained classifier by using the third feature so as to obtain a trained classifier; and obtaining a third feature to be recognized of a speech signal to be recognized, so as to determine whether the third feature to be recognized comprises a prepositive word.

Abstract: A custom tone and vocal synthesis method and apparatus, an electronic device, and a storage medium. The synthesis method comprises: training a first neural network by means of a speaker record sample to obtain a speaker recognition model, the output training result of the first neural network being a speaker vector sample (S102); training a second neural network by means of an unaccompanied vocal singing sample and the speaker vector sample to obtain an unaccompanied singing synthesis model (S104); inputting a speaker record to be synthesized into the speaker recognition model to obtain speaker information output by the intermediate hidden layer of the speaker recognition model (S106); and inputting unaccompanied singing music information to be synthesized and the speaker information into the unaccompanied singing synthesis model to obtain a synthesized custom tone and vocal (S108).