A method of speaker recognition comprises: receiving an audio signal comprising speech; performing a biometric process on a first part of the audio signal, wherein the first part of the audio signal extends over a first time period; obtaining a speaker recognition score from the biometric process for the first part of the audio signal; performing a biometric process on a plurality of second parts of the audio signal, wherein the second parts of the audio signal are successive sections of the first part of the audio signal, and wherein each second part of the audio signal extends over a second time period and the second time period is shorter than the first time period; obtaining a respective speaker recognition score from the biometric process for each second part of the audio signal; and determining whether there has been a speaker change based on the respective speaker recognition scores for successive second parts of the audio signal.

The present invention relates to a system and method for assessing the cognitive style of a person. The system comprises an input interface (12) for receiving speech spoken by the person, a language processor (16) for analyzing the speech to identify predetermined natural language elements, and a style identifier (18, 18) for identifying the cognitive style of the person based on the identified natural language elements.

Verbal language analysis is provided to users. The user enrolls or subscribes for verbal language analysis or analytics. The user carries out or conducts a conversation with a third party. An intelligence device associated with the user records the conversation. The intelligence device performs verbal language analysis on the conversation. The verbal language analysis generates individual metrics for verbal factors of energy, word count, inflection, tone (e.g. pitch and sentiment), rate, and/or the like. A verbal intelligence index is determined from the individual metrics using aggregation, averaging, weighted averaging, and/or the like. An interface component generates views to display to the user for review of the conversation to facilitate better verbal performance during current and in future conversations.

The invention relates to a method and an apparatus for tracking a fundamental frequency of a voice signal. A sampling device samples a voice signal of a test person for a predetermined period of time (S1), thus obtaining sampling data of the voice signal, forms a data packet from the sampling data (S2), and sends the data packet to a calculating device (S3). The calculating device receives the data packet (S5) and calculates a fundamental frequency of the voice signal by means of the sampling data contained in the data packet (S6). The sampling device sets a timer based on the fundamental frequency calculated by the calculating device and outputs a trigger signal upon expiration of the timer (S11).

A time-varying pitch of a signal may be estimated by processing a sequence of frames of the speech signal. An estimated fractional chirp rate may be computed for each frame of the sequence of frames, and the estimated fractional chirp rates may be used to compute a pitch template for the sequence, where the pitch template indicates the time-varying pitch of the signal subject to a scale factor. A first pitch estimate for each frame of the sequence of frames may be computed by computing a scale factor and multiplying the pitch template by the scale factor. A second pitch estimate may be computed from the first pitch estimate by identifying peaks in the frequency representations using the first pitch estimates and fitting a parametric function to the peaks.

Disclosed herein is a system for identifying and diagnosing sounds of infected wild birds and poultry. The system includes: a multi channel audio analysis device (MCAAD); and a sound collection unit connected to the MCAAD via a wired or wireless connection. The sound collection unit collects sounds of birds via a plurality of microphones, and information about the collected sounds is transmitted to the MCAAD via a relay.

A time-varying pitch of a signal may be estimated by processing a sequence of frames of the speech signal. An estimated fractional chirp rate may be computed for each frame of the sequence of frames, and the estimated fractional chirp rates may be used to compute a pitch template for the sequence, where the pitch template indicates the time-varying pitch of the signal subject to a scale factor. A first pitch estimate for each frame of the sequence of frames may be computed by computing a scale factor and multiplying the pitch template by the scale factor. A second pitch estimate may be computed from the first pitch estimate by identifying peaks in the frequency representations using the first pitch estimates and fitting a parametric function to the peaks.

A speech evaluation apparatus includes a memory, and a processor coupled to the memory and configured to generate a first input spectrum obtained by frequency transforming a first signal that is a signal of a first period, generate a second input spectrum obtained by frequency transforming a second signal that is the signal of a second period earlier than the first period, generate a processed spectrum obtained by transforming frequency of the second input spectrum based on a change ratio set in advance, calculate a correlation value between the first input spectrum and the processed spectrum, and determine a change amount of pitch frequency from the first signal to the second signal based on the change ratio and the correlation value.

The present document discloses a method and apparatus for compensating for a lost frame in a transform domain, comprising: calculating frequency-domain coefficients of a current lost frame using frequency-domain coefficients of one or more frames prior to the current lost frame, and performing frequency-time transform to obtain an initially compensated signal; and performing waveform adjustment, to obtain a compensated signal. Alternatively, extrapolation is performed for all or part of frequency points of the current lost frame using phases and amplitudes of corresponding frequency points of a plurality of previous frames to obtain phases and amplitudes of the corresponding frequency points of the current lost frame, to obtain frequency-domain coefficients of the corresponding frequency points, and frequency-time transform is performed to obtain a compensated signal. The above methods can be selected through a judgment algorithm to compensate for the current lost frame, thereby achieving a better compensation effect.

A social network system for pets comprises a sensor for detecting or collecting a pet's voices or body signals, a translation unit for comparing the detected pet's voices or body signals with the stored sample patterns, determining the pet's emotions or feelings by choosing one or many sample patterns which are most closely matched to the detected pet's voices or body signals, and a processing unit for performing one or many actions based on the determined pet's emotions or feelings.