Abstract: A method for employing pitch in a speech recognition engine. The process begins by building training models of selected speech samples, a process which begins by analyzing each sample as a sequential series of frames, each frame having a selected duration and overlap with adjacent frames. A pitch estimate of each frame is detected and recorded, and the pitch data is normalized, and the speech recognition parameters of the model are determined, after which the model is stored. Models are stored and updated for each of the set of training samples. The system is then employed to recognizing the speech content of a subject, which begins by analyzing the subject as a sequential series of frames, each frame having a selected duration and overlap with adjacent frames. A pitch estimate for each frame is detected and recorded, and the pitch data is normalized. Speech recognition techniques are then employed to recognize the content of the subject, employing the stored models.

Abstract: A method for searching a database to produce search results from queries likely to contain errors. The process begins by identifying database features likely to be useful in searching, and those features are employed to index the database. After receiving a query from a user, the system develops a rough score for the query, by extracting features from the query, assigning match scores to query features matching database features; and assigning approximation scores to query features amenable to approximation analysis with database features. The rough score is used to identify identifying a set of database records for further analysis. Those records are then subjected to a more detailed rescoring process, based on correspondence between individual query elements and individual record elements, and between the query and the database record content, taken as a whole. Based on the rescoring process, output is provided to the user.

Abstract: A method for non-text-based identification of a selected item of stored music. The first broad portion of the method focuses on building a music identification database. That process requires capturing a tag of the selected musical item, and processing the tag to develop reference key to the same. Then the tag is stored, together with the reference key and an association to the stored music. The database is built by collecting a multiplicity of tags. The second broad portion of the method is retrieving a desired item of stored music from the database. That process calls for capturing a query tag from a user, and processing the query tag to develop a query key to the same. The query tag is compared to reference keys stored in the database to identify the desired item of stored music.