Abstract: A hybrid markup language document (or “HMLD”) is scanned for a partition boundary. Content in the HMLD that precedes the partition boundary is discarded for simpler and faster processing.

Abstract: A hybrid markup language document (or “HMLD”) is scanned for a partition boundary. Content in the HMLD that precedes the partition boundary is discarded for simpler and faster processing.

Abstract: A hybrid markup language document (or “HMLD”) is scanned for a partition boundary. Content in the HMLD that precedes the partition boundary is discarded for simpler and faster processing.

Abstract: A hybrid markup language document (or “HMLD”) is scanned for a partition boundary. Content in the HMLD that precedes the partition boundary is discarded for simpler and faster processing.

Abstract: A process and system for partitioning hybrid markup language documents (HMLDs) is disclosed. Content from an HMLD is copied to one or more output markup language documents (MLDs), which may be well-formed or valid MLDs. The HMLD is segmented at partition boundaries within the document, while state information is recorded in a tag stack. The state information is used to complete the output MLD, which may be sent to a software module for processing. The HMLDs and MLDs may be well-formed or valid extensible markup language (XML) documents.

Abstract: A process and system for partitioning hybrid markup language documents (HMLDs) is disclosed. Content from an HMLD is copied to one or more output markup language documents (MLDs), which may be well-formed or valid MLDs. The HMLD is segmented at partition boundaries within the document, while state information is recorded in a tag stack. The state information is used to complete the output MLD, which may be sent to a software module for processing. The HMLDs and MLDs may be well-formed or valid extensible markup language (XML) documents.

Abstract: A speech synthesis system can select recorded speech fragments, or acoustic units, from a very large database of acoustic units to produce artificial speech. The selected acoustic units are chosen to minimize a combination of target and concatenation costs for a given sentence. However, as concatenation costs, which are measures of the mismatch between sequential pairs of acoustic units, are expensive to compute, processing can be greatly reduced by pre-computing and aching the concatenation costs. Accordingly, a method is disclosed for constructing an efficient concatenation cost database by synthesizing a large body of speech, identifying the acoustic unit sequential pairs generated and their respective concatention costs, and storing those concatenation costs likely to occur.

Abstract: A speech synthesis system can select recorded speech fragments, or acoustic units, from a very large database of acoustic units to produce artificial speech. The selected acoustic units are chosen to minimize a combination of target and concatenation costs for a given sentence. However, as concatenation costs, which are measures of the mismatch between sequential pairs of acoustic units, are expensive to compute, processing can be greatly reduced by pre-computing and caching the concatenation costs. Unfortunately, the number of possible sequential pairs of acoustic units makes such caching prohibitive. However, statistical experiments reveal that while about 85% of the acoustic units are typically used in common speech, less than 1% of the possible sequential pairs of acoustic units occur in practice.

Abstract: A method and system that allows users, or maintainers, of a speech-based application to revise the phonetic transcription of words in a phonetic dictionary, or to add transcriptions for words not yet present in the dictionary. The application is assumed to communicate with the user or maintainer audibly by means of speech recognition and/or speech synthesis systems, both of which rely on a dictionary of phonetic transcriptions to accurately recognize speech and pronunciation of a given word. The method automatically determines the phonetic transcription based on the word's spelling and the recorded preferred pronunciation, and updates the dictionary accordingly. Moreover, both speech synthesis and recognition performance are improved through use of the updated dictionary.