Retrieving spoken documents by combining multiple index sources · References · Cited By · Index Terms · Recommendations · Comments · Information & Contributors.
This paper presents domain-independent methods of spoken document retrieval. Both a continuous-speech large vocab- ulary recognition system, and a phone-lattice ...
This paper presents domain-independent methods of spoken document retrieval. Both a continuous-speech large vocabulary recognition system, ...
Different ways of combining them are investigated, and it is shown that the best of these can increase retrieval average precision for a speakerindependent ...
This paper presents domain-independent methods of spoken document retrieval. Both a continuous-speech large vocabulary recognition system, ...
Jun 22, 2018 · A more efficient method would be to collect the data for each host from all the data sources, merge them, then index the fully merged document directly.
Missing: Spoken | Show results with:Spoken
In this guide, you learn towards setting up an agent that can effectively answer different types of questions over a larger set of documents.
We have a guide to creating a unified query framework over your indexes which shows you how to run queries across multiple indexes. And also over structured ...
Jan 22, 2013 · Having 1 index for each model will significantly increase the number of your shards as 1 index will use 5 shards, 5 data models will use 25 shards.
Aug 15, 2019 · One last issue is the quality of the scan and the resultant OCR-ing. You will get better results if you have larger text and higher resolution ...
Missing: Spoken | Show results with:Spoken