The invention relates to a muffler which includes a first expansion chamber, a second expansion chamber, a resonator chamber, and an inlet pipe having a first open end and a second open end. The first open end of the inlet pipe is inserted into the first expansion chamber so as to communicate with the latter. A resonator pipe runs substantially in a coaxial relationship with the inlet pipe so as to establish communication between the first expansion chamber and the resonant chamber. A return pipe is disposed between the resonator chamber and the second expansion chamber and passes through the first expansion chamber for establishing communication between the first expansion chamber and the second expansion chamber. An outlet pipe communicates with the second expansion chamber. The improvement comprises that said return pipe has an open end and is inserted with the open end into said resonator chamber, while the inserted open end thereof is sealed with a plug. A portion of the return pipe, passing through the first expansion chamber and the resonator chamber, is provided with at least a throughhole.
A speech recognition method for use in a multimodal input system comprises receiving a multimodal input comprising digitized speech as a first modality input and data in at least one further modality input. Features in the speech and in the data in at least one further modality are identified. The identified features in the speech and in the data are used in the recognition of words by comparing the identified features with states in models for the words. The models have states for the recognition of speech and for words having features in at least one further modality associated with the words, the models also have states for the recognition of events in the further modality or each further modality.
The present invention relates to a speech recognition method and a system for a speech-controllable telephone in which a value is computed (2) for a reference word with a speech recognizer (8) on the basis of a word uttered by a user, and a recognition resolution (6a, 6b) is made on the basis of said value. Prior to making said recognition resolution, it is found out (3) if repetition of a previous word is in question, and if so, a new value is computed (5) for the reference word on the basis of the value computed by the speech recognizer and of a value in the memory, computed earlier for the reference word, and a recognition resolution (6a, 6b) is made on the basis of said computed new value.
A method and apparatus for automatic recognition of speech adapts to a particular speaker by using adaptation data to develop a transformation through which speaker independent models are transformed into speaker adapted models. The speaker adapted models are then used for speaker recognition and achieve better recognition accuracy than non-adapted models. In a further embodiment, the transformation-based adaptation technique is combined with a known Bayesian adaptation technique.
An isolated speech word recognizer for recognizing an input pattern as one of a plurality of known patterns, comprising a similarity information storing unit for storing similarity information representing the degree of significance of a feature in each of the known patterns for recognizing thereof, and a most similar pattern determining unit for determining one of the plurality of known patterns as the most similar pattern to the input pattern by the use of the similarity information, whereby the recognition performance is improved.
Distances are measured between vectors representing speech and a stored reference template. Frequency distributions of the distance measurements are generated by counting how many times a particular reference template resulted in the lowest local distance. The numbers in the counters indicate regions (successive vectors) in a reference template that are good matches for speech input.
