Mariana Lourenço


Towards Speaker Verification for Crowdsourced Speech Collections
John Mendonca | Rui Correia | Mariana Lourenço | João Freitas | Isabel Trancoso
Proceedings of the Thirteenth Language Resources and Evaluation Conference

Crowdsourcing the collection of speech provides a scalable setting to access a customisable demographic according to each dataset’s needs. The correctness of speaker metadata is especially relevant for speaker-centred collections - ones that require the collection of a fixed amount of data per speaker. This paper identifies two different types of misalignment present in these collections: Multiple Accounts misalignment (different contributors map to the same speaker), and Multiple Speakers misalignment (multiple speakers map to the same contributor). Based on state-of-the-art approaches to Speaker Verification, this paper proposes an unsupervised method for measuring speaker metadata plausibility of a collection, i.e., evaluating the match (or lack thereof) between contributors and speakers. The solution presented is composed of an embedding extractor and a clustering module. Results indicate high precision in automatically classifying contributor alignment (>0.94).


ASAP: Automatic Semantic Alignment for Phrases
Ana Alves | Adriana Ferrugento | Mariana Lourenço | Filipe Rodrigues
Proceedings of the 8th International Workshop on Semantic Evaluation (SemEval 2014)