Abstract: A voice generation method and apparatus, an electronic device, and a computer readable storage medium. Said method comprises: performing speaker segmentation on an original voice to determine starting time and ending time of each speaking voice segment in the original voice, so as to obtain segmented voices; determining a voiceprint feature vector corresponding to each speaking voice segment in the original voice; converting a text corresponding to each speaking voice segment in the original voice into a target language text, to obtain a target language text corresponding to each speaking voice segment in the original voice; and generating a target voice on the basis of the starting time and the ending time of each speaking voice segment in the original voice, the voiceprint feature vectors corresponding to the speaking voice segments and the target language texts corresponding to the speaking voice segments.

Abstract: Embodiments of the present disclosure disclose an audio content recognition method and apparatus, an electronic device and a non-transitory computer-readable medium. A specific implementation of the method includes: obtaining a voice fragment collection and a non-voice fragment collection by segmenting audio; determining a type and language information of each voice fragment in the voice fragment collection; obtaining, for each voice fragment in the voice fragment collection, a first recognition result by performing voice recognition on the voice fragment based on the type and the language information of the voice fragment. In the implementation, speaking and music fragments in the audio are recognized by different models, so that two audio contents may both have better recognition effects. Moreover, audio of different language contents is recognized by using different models, thereby further improving a voice recognition effect.

Abstract: Embodiments of the present disclosure disclose an audio content recognition method and apparatus, an electronic device and a non-transitory computer-readable medium. A specific implementation of the method includes: obtaining a voice fragment collection and a non-voice fragment collection by segmenting audio; determining a type and language information of each voice fragment in the voice fragment collection; obtaining, for each voice fragment in the voice fragment collection, a first recognition result by performing voice recognition on the voice fragment based on the type and the language information of the voice fragment. In the implementation, speaking and music fragments in the audio are recognized by different models, so that two audio contents may both have better recognition effects. Moreover, audio of different language contents is recognized by using different models, thereby further improving a voice recognition effect.