A multifunctional microphone, includes a controlling mainboard; a sound collector electrically connected with the controlling mainboard; a speaker electrically connected with the controlling mainboard; and a sound adjusting module arranged on the controlling mainboard and configured to adjust sound collected by the sound collector.

A method for accompaniment purity class evaluation and related devices are provided. Multiple first accompaniment data and a label corresponding to each of the multiple first accompaniment data are obtained, the label being used to indicate that corresponding first accompaniment data is pure instrumental accompaniment data or instrumental accompaniment data with background noise. An audio feature of each of the multiple first accompaniment data is extracted. Model training is performed according to the audio feature of each of the multiple first accompaniment data and the label corresponding to each of the multiple first accompaniment data, to obtain a neural network model for accompaniment purity class evaluation, a model parameter of the neural network model being determined according to an association relationship between the audio feature of each of the multiple first accompaniment data and the label corresponding to each of the multiple first accompaniment data.

An accompaniment classification method and apparatus is provided. The method includes the following. A first type of audio features of a target accompaniment is obtained (S301, S401). Data normalization is performed on each kind of audio features in the first type of audio features of the target accompaniment to obtain a first feature-set of the target accompaniment and the first feature-set is input into a first classification model for processing (S302, S402). A first probability value output by the first classification model for the first feature-set is obtained (S303, S403). An accompaniment category of the target accompaniment is determined to be a first category of accompaniments when the first probability value is greater than a first classification threshold (S404). The accompaniment category of the target accompaniment is determined to be other categories of accompaniments when the first probability value is less than or equal to the first classification threshold.

The disclosure provides a method and an apparatus for song generation. A text input may be received. A topic and an emotion may be extracted from the text input. A melody may be determined according to the topic and the emotion. Lyrics may be generated according to the melody and the text input. A song may be generated at least according to the melody and the lyrics.

Provided is a method for processing audio including: acquiring an accompaniment audio signal and a voice signal of a current to-be-processed musical composition; determining a target reverberation intensity parameter value of the acquired accompaniment audio signal, wherein the target reverberation intensity parameter value is configured to indicate a rhythm speed, an accompaniment type, and a performance score of a singer of the current to-be-processed musical composition; and reverberating the acquired vocal signal based on the target reverberation intensity parameter value.

Disclosed herein are method, system, and computer program product embodiments for performing the continuous tuning of received audio input from an earpiece or microphone especially customized for karaoke singing, wherein the audio input may be mixed with user-selected song input, and the joint mixed input is independently altered in the frequency domain for output to an earpiece worn by a user as well as separately for an additional audio output to an external connected speaker, for an optimal karaoke experience.

A pitch adjustment method and apparatus, and a computer storage medium are provided. the fundamental frequency sequence of the singing sound of the user is obtained, the pitch difference between each candidate melody file and the fundamental frequency sequence at each corresponding time point is calculated, and the sum of all pitch differences of each candidate melody file is calculated. The candidate melody file with the minimum sum is determined as the target melody file, and the pitch of the accompaniment file of the target song is adjusted according to the pitch difference between the target melody file and the original melody file of the target song.

A video processing device, which inputs a piece of music and selects and outputs one video of a plurality of video sources, is provided. The video processing device includes a music analyzing part, which analyzes a progress of the piece of music; a video selecting part, which selects the one video from the plurality of video sources; and an output part, which outputs the one video at a timing corresponding to the progress of the piece of music that has been analyzed by the music analyzing part.

A method for processing a voice signal by an electronic system to create a song is disclosed. The method comprises the steps in the electronic system of acquiring an input singing voice recording (11); estimating a musical key (15b) and a Tempo (15a) from the singing voice recording (11); defining a tuning control (16) and a timing control (17) able to align the singing voice recording (11) with the estimated musical key (15b) and Tempo (15a); applying the tuning control (16) and the timing control (17) to the singing voice recording (11) so that an aligned voice recording (20) is obtained. Next, the method comprises the step of generating an music accompaniment (23) as function of the estimated musical key (15b) and Tempo (15a) and an arrangement database (22) and mixing the aligned voice recording (20) and the music accompaniment (23) to obtain the song (12). A system a server and a device are also disclosed.

An information processing device, a tempo detection device and a video processing system are provided. A beat of a piece of performed music is detected from a musical viewpoint. The information processing device includes: an acquisition part that acquires samples of musical sound signals in a time series; an evaluation part that has an adaptive filter using the acquired samples of the musical sound signals as reference signals and using samples of musical sound signals acquired a predetermined time earlier than the samples of the musical sound signals as input signals; and a tempo determination part that sequentially inputs the samples of the musical sound signals to the adaptive filter and determines a tempo corresponding to a musical sound based on a filter coefficient when a value of the filter coefficient of the adaptive filter converges.