Abstract: A computerized method of detecting a target word in a speech signal. A speech recognition engine and a previously constructed phoneme model is provided. The speech signal is input into the speech recognition engine. Based on the phoneme model, the input speech signal is indexed. A time-ordered list is stored representing n-best phoneme candidates of the input speech signal and phonemes of the input speech signal in multiple phoneme frames. The target word is transcribed into a transcription of target phonemes. The time-ordered list of n-best phoneme candidates is searched for a locus of said target phonemes. While searching, scoring is based on the ranking of the phoneme candidates among the n-best phoneme candidates and based on the number of the target phonemes found. A composite score of the probability of an occurrence of the target word is produced. When the composite score is higher than a threshold, start and finish times are output which bound the locus.

Abstract: A computerized method of detecting a target word in a speech signal. A speech recognition engine and a previously constructed phoneme model is provided. The speech signal is input into the speech recognition engine. Based on the phoneme model, the input speech signal is indexed. A time-ordered list is stored representing n-best phoneme candidates of the input speech signal and phonemes of the input speech signal in multiple phoneme frames. The target word is transcribed into a transcription of target phonemes. The time-ordered list of n-best phoneme candidates is searched for a locus of said target phonemes. While searching, scoring is based on the ranking of the phoneme candidates among the n-best phoneme candidates and based on the number of the target phonemes found. A composite score of the probability of an occurrence of the target word is produced. When the composite score is higher than a threshold, start and finish times are output which bound the locus.

Abstract: A method for processing an analog speech signal for speech recognition. The analog speech signal is sampled to produced a sampled speech signal. The sampled speech signal is framed into multiple frames of the sampled speech signal. The absolute value of the sampled speech signal is integrated within the frames and respective integrated-absolute values of the frames are determined. Based on the integrated-absolute values, the sampled speech signal is cut into segments of non-uniform duration. The segments are not as yet identified as parts of speech prior to and during the cutting.

Abstract: A computerized method for speech recognition in a computer system. Reference word segments are stored in memory. The reference word segments when concatenated form spoken words in a language. Each of the reference word segments is a combination of at least two phonemes, including a vowel sound in the language. A temporal speech signal is input and digitized to produced a digitized temporal speech signal The digitized temporal speech signal is transformed piecewise into the frequency domain to produce a time and frequency dependent transform function. The energy spectral density of the temporal speech signal is proportional to the absolute value squared of the transform function. The energy spectral density is cut into input time segments of the energy spectral density. Each of the input time segments includes at least two phonemes including at least one vowel sound of the temporal speech signal.