Voice Information Retrieval In Collaborative Information Seeking
This addresses the lack of voice search support for collaborative tasks, which is an incremental improvement for users in group information-seeking contexts.
The paper tackled the problem of enabling collaborative information seeking via voice queries by integrating automatic speech recognition with a collaborative system, achieving 81.25% transcription accuracy in simulations.
Voice information retrieval is a technique that provides Information Retrieval System with the capacity to transcribe spoken queries and use the text output for information search. CIS is a field of research that involves studying the situation, motivations, and methods for people working in a collaborative group for information seeking projects, as well as building a system for supporting such activities. Humans find it easier to communicate and express ideas via speech. Existing voice search like Google and other mainstream voice search does not support collaborative search. The spoken speeches passed through the ASR for feature extraction using MFCC and HMM, Viterbi algorithm precisely for pattern matching. The result of the ASR is then passed as input into CIS System, results is then filtered to have an aggregate result. The result from the simulation shows that our model was able to achieve 81.25% transcription accuracy.