A speech recognition system includes speech presence detection which uses a first level threshold of ambient noise/silence above which speech start is decided for a signal. Speech end is decided when the signal falls to a second threshold equal to the first, unless a predetermined time interval of speech is exceeded after start, causing a corrected second threshold to be calculated and used.

Speech recognition system for an automotive vehicle

Voice activity detector (VAD) for use in an LPC coder in a mobile radio system uses autocorrelation coefficient R 0 , R 1 . . . of the input signal, weighted and combined, to provide a measure M which depends on the power within that part of the spectrum containing no noise, which is thresholded against a variable threshold to provide a speech/no speech logic output. The measure is formula (I), where H i are the autocorrelation coefficients of the impulse response of an Nth order FIR inverse noise filter derived from LPC analysis of previous non-speech signal frames. Threshold adaption and coefficient update are controlled by a second VAD response to rate of spectral change between frames.

Voice activity detection

A distributed control apparatus and method is disclosed to maintain the network stability in a packet switching local area network under changing traffic load conditions, by controlling the size of the packets transmitted by each node. The invention monitors the present information flow rate in the network and computes an average packet length which it then uses to adjust the size of the variable length data field in each message frame. In this manner, network flow control can be achieved without forcing data terminals connected to the nodes of the network to adjust their speed. The invention is applicable to a wide variety of local area network protocols for both ring and bus architectures.

Adaptive packet length traffic control in a local area network

A voice activity detector suitable for deployment in a mobile phone apparatus is disclosed. An advantage of the voice activity detector is that it is better able to provide a decision (79) as to whether an input signal (19) consists of noise (which it is not desired to transmit) or comprises speech or information tones (which are required to be transmitted), especially in noisy environments. The voice activity detector includes a number of components, in particular an auxiliary voice activity detector (3). The auxiliary voice activity detector (3) distinguishes between noise and speech on the basis that the spectrum of speech changes more rapidly than that of noise. This results in the auxiliary detector (3) rarely mistaking a speech signal to be a noise signal. Hence, a very reliable noise template (421) is obtained. For this reason, the auxiliary detector (3) is also useful in noise reduction applications. The voice activity detector also uses a neural net classifier (7).

Voice activity detector

This paper describes a highly sensitive speech detector and a high-speed voiceband data classifier capable of discriminating between speech and voiceband data of a 4.8 kbit/s 8-phase PSK and 4.8 kbit/s 8-point QAM, and a 9.6 kbit/s 16-point QAM as described in a CCITT recommendation. The presence of a speech signal is detected by analyzing short-time energies, zero-crossing rates, and sign bit sequences of the input signal. The proposed speech detector, with a short hangover time of 32 ms, is able to reduce the average talk spurt activity in an international satellite link to 36 percent. This detector can also classify the detected speech into narrow-band or wide-band spectrum sounds or a low power sound for a variable rate ADPCM encoding. Discrimination between speech and high-speed voiceband data is based on short-time energies, a zeros-crossing rate and linear prediction coefficients of an adaptive predictor. Classification among a 4.8 kbit/s 8-phase PSK and 8-point QAM, and a 9.6 kbit/s 16-point QAM can also be performed by an average prediction gain and a coefficient of variation of the short-term amplitude distribution of the input signal. Discrimination of voiceband data was performed successfully, and erroneous discrimination of talk spurt of telephone speech as voiceband data were, respectively, four times for two two-party conversations lasting 5 minutes in an international satellite link. This is equivalent to less than 0.09 percent of the conversation time.

Highly Sensitive Speech Detector and High-Speed Voiceband Data Discriminator in DSI-ADPCM Systems

This paper proposes two dynamic-type speech detectors; their performances are described also by means of in-field experimental results. The two detectors are based on the same operational principle: the presence of the speech signal is detected by analyzing the dynamic variations of the short-time-power of the channel signal.

Digital Dynamic Speech Detectors

A system and method for detecting the presence of useful speech information in telephone voice channels capable of containing noise as well as such useful speech information for optimizing the telephone transmission of such speech information. Two segments of the envelope of a given voice channel are compared against each other over two different time domains in order to determine if a predetermined magnitude of difference exists between these envelopes. The presence of such magnitude of difference is indicative of the presence of such useful speech information in the voice channel thereby enabling transmission thereof by the system, whereas the absence of such magnitude of difference is indicative of the presence of solely noise thereby preventing the transmission thereof by the system.

Method and apparatus for detecting the presence of a speech signal on a voice channel signal

An all digital system, labeled PCM.RR. is presented, which enables the doubling of traffic capacity of PCM links. This is obtained, although keeping the transmission quality impairment very close to the normal PCM standards, by properly using "Adaptive Quantization" and "Speech Interpolation" performed by means of a "Speech Detector" that works directly on the A -law compressed digital signal.

Alcide Molinari

Papers

Digital Dynamic Speech Detectors

Method and apparatus for detecting the presence of a speech signal on a voice channel signal

Bit Rate Per Channel Halving in PCM Multiplexes by Speech Interpolation and Adaptive Quantization