The intelligent accompaniment generating system includes an input module, an analysis module, a generation module and a musical equipment. The input module is configured to receive a musical pattern signal derived from a raw signal. The analysis module is configured to analyze the musical pattern signal to extract a set of audio features, wherein the input module is configured to transmit the musical pattern signal to the analysis module. The generation module is configured to obtain a playing assistance information having an accompaniment pattern from the analysis module, wherein the accompaniment pattern has at least two parts having different onsets therebetween, and each onsets of the at least two parts is generated by an algorithm according to the set of audio features. The musical equipment includes a digital amplifier configured to output an accompaniment signal according to the accompaniment pattern.

Provided a haptic feedback method, including: step S1 of algorithmically training an audio clip containing a known audio event type to obtain an algorithm model; and step S2 of obtaining an audio, identifying the audio by the algorithm model to obtain different audio event types in this audio, matching, according to a preset rule, the audio event types with different vibration effects as a haptic feedback and outputting the haptic feedback. Compared with the related art, the present haptic feedback method provides users with real-time haptic feedback when applied to a mobile electronic product, thereby achieving excellent use experience of the mobile electronic product.

A method, computer program, and computer system is provided for converting a singing voice of a first person associated with a first speaker to a singing voice of a second person using a speaking voice of the second person associated with a second speaker. A context associated with one or more phonemes corresponding to the singing voice of a first person is encoded, and the one or more phonemes are aligned to one or more target acoustic frames based on the encoded context. One or more mel-spectrogram features are recursively generated from the aligned phonemes, the target acoustic frames, and a sample of the speaking voice of the second person. A sample corresponding to the singing voice of a first person is converted to a sample corresponding to the second singing voice using the generated mel-spectrogram features.

A method, computer program, and computer system is provided for converting a singing first singing voice associated with a first speaker to a second singing voice associated with a second speaker. A context associated with one or more phonemes corresponding to the first singing voice is encoded, and the one or more phonemes are aligned to one or more target acoustic frames based on the encoded context. One or more mel-spectrogram features are recursively generated from the aligned phonemes and target acoustic frames, and a sample corresponding to the first singing voice is converted to a sample corresponding to the second singing voice using the generated mel-spectrogram features.

A method and system for determining a compact semantic representation of a digital audio signal using a computer-based system by calculating at least one low-level feature matrix from the digital audio signal; processing the low-level feature matrix or matrices using pre-trained machine learning engines including an ensemble of modules, wherein each module in the ensemble is trained to predict a one of a plurality of high-level feature values; and concatenating the obtained plurality of high-level feature values into a descriptor vector. The calculated descriptor vectors can be used alone, or in an arbitrary or temporally ordered combination with further descriptor vectors calculated from different audio signals extracted from the same music track, as a compact semantic representation of the respective music track.

A mobile device responds in real time to media content presented on a media device, such as a television. The mobile device captures temporal fragments of audio-video content on its microphone, camera, or both and generates corresponding audio-video query fingerprints. The query fingerprints are transmitted to a search server located remotely or used with a search function on the mobile device for content search and identification. Audio features are extracted and audio signal global onset detection is used for input audio frame alignment. Additional audio feature signatures are generated from local audio frame onsets, audio frame frequency domain entropy, and maximum change in the spectral coefficients. Video frames are analyzed to find a television screen in the frames, and a detected active television quadrilateral is used to generate video fingerprints to be combined with audio fingerprints for more reliable content identification.

The intelligent accompaniment generating system includes an input module, an analysis module, a generation module and a musical equipment. The input module is configured to receive a musical pattern signal derived from a raw signal. The analysis module is configured to analyze the musical pattern signal to extract a set of audio features, wherein the input module is configured to transmit the musical pattern signal to the analysis module. The generation module is configured to obtain a playing assistance information having an accompaniment pattern from the analysis module, wherein the accompaniment pattern has at least two parts having different onsets therebetween, and each onsets of the at least two parts is generated by an algorithm according to the set of audio features. The musical equipment includes a digital amplifier configured to output an accompaniment signal according to the accompaniment pattern.

A computer-implemented sound signal generation method includes: obtaining a first sound source spectrum of a sound signal to be generated; obtaining a first spectral envelope of the sound signal; and estimating fragment data representative of samples of the sound signal based on the obtained first sound source spectrum and the obtained first spectral envelope.

A device is provided for capturing vibrations produced by an object such as a musical instrument such as a drum head of a drum kit. The device comprises a detectable element, such as a ferromagnetic element, such as a metal shim and a sensor spaced apart from and located relative to the musical instrument. The detectable element is located between the sensor and the musical instrument. When the musical instrument vibrates, the sensor remains stationary and the detectable element is vibrated relative to the sensor by the musical instrument.

A voice processing method realized by a computer includes compressing forward a first steady period of a plurality of steady periods in a voice signal representing voice, and extending forward a transition period between the first steady period and a second steady period of the plurality of steady periods in the voice signal. Each of the plurality of steady periods is a period in which acoustic characteristics are temporally stable. The second steady period is a period immediately after the first steady period and has a pitch that is different from a pitch of the first steady period.