Unconstrained keyword spotting using phone lattices with application to spoken document retrieval

Foote, Jonathan; Young, S.; Jones, Gareth; Jones, Karen Spärck

doi:10.1006/csla.1997.0027

Cited by 21 publications

(15 citation statements)

References 16 publications

(24 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…While our purpose was to maximize the utility of the retrieved lattices as quickly as possible, future work might extend this approach by reranking the returned list with a more costly lattice scanning system [3]. We also hope to explore larger collection sizes.…”

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Fast Unconstrained Audio Search in Numerous Human Languages

Olsson

Wintrode

Lee

2007

2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07

View full text Add to dashboard Cite

We present a system to index and search conversational speech using a scoring heuristic on the expected posterior counts of phone n-grams in recognition lattices. We report signi cant improvements in retrieval effectiveness on ve human languages over a strong 1-best baseline. The method is shown to improve the utility (mean average precision) of the retrieved lattices' rank order and to do so with a search cost negligible compared to the fastest yet known methods for the linear scanning of phonetic lattices.

show abstract

Section: Resultsmentioning

confidence: 99%

“…Research in vocabulary independent SDR has largely focused on subword indexing methods [2] and ef ciently searching more complex representations of the recognition hypotheses, such as phonetic lattices [3,4]. Because a linear search through many lattices is still costly, two-stage search systems have also been considered.…”

Section: Introductionmentioning

confidence: 99%

Fast Unconstrained Audio Search in Numerous Human Languages

Olsson

Wintrode

Lee

2007

2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07

View full text Add to dashboard Cite

show abstract

“…It has previously been demonstrated that allowing for phoneme confusability can significantly increase spoken term detection performance on onebest phoneme transcripts (Chaudhari and Picheny, 2007;Schone et al, 2005) and in phonemic lattices (Foote et al, 1997). These methods work by allowing weighted substitution costs in minimumedit-distance matching.…”

Section: Incorporating Query Degradationsmentioning

confidence: 99%

Phrase-based query degradation modeling for vocabulary-independent ranked utterance retrieval

Olsson

Oard

2009

Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Com

View full text Add to dashboard Cite

This paper introduces a new approach to ranking speech utterances by a system's confidence that they contain a spoken word. Multiple alternate pronunciations, or degradations, of a query word's phoneme sequence are hypothesized and incorporated into the ranking function. We consider two methods for hypothesizing these degradations, the best of which is constructed using factored phrasebased statistical machine translation. We show that this approach is able to significantly improve upon a state-of-the-art baseline technique in an evaluation on held-out speech. We evaluate our systems using three different methods for indexing the speech utterances (using phoneme, phoneme multigram, and word recognition), and find that degradation modeling shows particular promise for locating out-of-vocabulary words when the underlying indexing system is constructed with standard word-based speech recognition.

show abstract

“…The Video Mail Retrieval (Foote, 1997) achieves audio and video document retrieval by the keyword-spotting algorithm. Another example is the Infomedia digital video library project (Hauptmann, 1997) that aims to offer effective search and retrieval of relevant information from digital library.…”

Section: Spoken Document Retrievalmentioning

confidence: 99%

“…Another example is the Infomedia digital video library project (Hauptmann, 1997) that aims to offer effective search and retrieval of relevant information from digital library. SDR has evolved from the early keyword-spotting based retrieval (Foote, 1997 andJones et. al., 1996b) to more recent systems based on large scale broadcast news transcription systems working in conjunction with information retrieval systems (Thong et.…”

Section: Spoken Document Retrievalmentioning

confidence: 99%

Multi-Scale Spoken Document Retrieval for Cantonese Broadcast News

Meng

Ching

2004

International Journal of Speech Technology

View full text Add to dashboard Cite

This paper presents the application of a multi-scale paradigm to Chinese spoken document retrieval (SDR) for improving retrieval performance. Multi-scale refers to the use of both words and subwords for retrieval. Words are basic units in a language that carry lexical meaning and subword units (such as phonemes, syllables or characters) are building components for words. Retrieval using subword indexing units is found to perform better than words because of the robustness of subword units to out-of-vocabulary (OOV) words during speech recognition and ambiguities in word segmentation. Experimental results have demonstrated that subword bigrams can bring improvement in retrieval performance over words (~9.56%). Application of multi-scale fusion to SDR aims at combining the lexical information of words and the robustness of subwords. This work presents the first detailed investigation for a Cantonese broadcast news retrieval task using two different multi-scale fusion approaches: pre-retrieval fusion and post-retrieval fusion.Multi-scale retrieval using both words and syllable bigrams achieve improvement in retrieval performance (~1.90%) over retrieval on the composite scales.

show abstract

Unconstrained keyword spotting using phone lattices with application to spoken document retrieval

Cited by 21 publications

References 16 publications

Fast Unconstrained Audio Search in Numerous Human Languages

Fast Unconstrained Audio Search in Numerous Human Languages

Phrase-based query degradation modeling for vocabulary-independent ranked utterance retrieval

Multi-Scale Spoken Document Retrieval for Cantonese Broadcast News

Contact Info

Product

Resources

About