Abstract: Embodiments of this application provide a volume adjustment method and an electronic device. The volume adjustment method includes: receiving target volume used when a media playing device plays content; obtaining an audio signal, where the audio signal includes a first signal and a second signal, the first signal is a sound signal that is collected by a wearable device worn by a user and that is generated when the media playing device plays the content, and the second signal is a noise signal collected by the wearable device; determining adjusted volume based on the audio signal and the target volume; and sending the adjusted volume to a target device through a communication connection to the target device, where the adjusted volume is used to update volume used when the media playing device plays the content.

Abstract: This application discloses a sound effect adjustment method and an electronic device. In the method, a first electronic device that plays first audio may indicate a second electronic device to start up an audio collection apparatus, to collect an ambient sound and obtain ambient audio. The second electronic device is an electronic device with a highest possibility that a user carries the electronic device. Based on the first audio and the ambient audio, the first electronic device may determine a difference between a listening sound effect of the first audio at a location of the second electronic device and an optimal sound effect. The first electronic device may adjust an audio parameter for playing the first audio, so that the listening sound effect of the first audio at the location of the second electronic device reaches the optimal sound effect.

Abstract: A speech enhancement method includes determining a first spectral subtraction parameter based on a power spectrum of a speech signal containing noise and a power spectrum of a noise signal, determining a second spectral subtraction parameter based on the first spectral subtraction parameter and a reference power spectrum, and performing, based on the power spectrum of the noise signal and the second spectral subtraction parameter, spectral subtraction on the speech signal containing noise, where the reference power spectrum includes a predicted user speech power spectrum and/or predicted environmental noise power. Regularity of a power spectrum feature of a user speech of a terminal device and/or regularity of a power spectrum feature of noise in an environment in which a user is located are considered.

Abstract: A speech enhancement method includes determining a first spectral subtraction parameter based on a power spectrum of a speech signal containing noise and a power spectrum of a noise signal, determining a second spectral subtraction parameter based on the first spectral subtraction parameter and a reference power spectrum, and performing, based on the power spectrum of the noise signal and the second spectral subtraction parameter, spectral subtraction on the speech signal containing noise, where the reference power spectrum includes a predicted user speech power spectrum and/or predicted environmental noise power. Regularity of a power spectrum feature of a user speech of a terminal device and/or regularity of a power spectrum feature of noise in an environment in which a user is located are considered.

Abstract: A method for speech command detection comprises extracting speech features from a speech signal inputted into a system, converting the speech features into a word sequence, obtaining time durations of speech segments corresponding to the respective non-command words and an acoustic score of each of the command word candidates, calculating rhythm features of the speech signal based on the time durations, and recognizing a speech corresponding to the at least one command word candidates as a speech command directed to the system or a speech not directed to the system based on the acoustic score and the rhythm features. The word sequence comprises at least two successive non-command words and at least one command word candidate. The rhythm features describe a similarity of time durations of speech segments corresponding to the respective non-command words, and/or a similarity of energy variations of the speech segments corresponding to the respective non-command words.