22,798 research outputs found
Improving Multi-Scale Aggregation Using Feature Pyramid Module for Robust Speaker Verification of Variable-Duration Utterances
Currently, the most widely used approach for speaker verification is the deep
speaker embedding learning. In this approach, we obtain a speaker embedding
vector by pooling single-scale features that are extracted from the last layer
of a speaker feature extractor. Multi-scale aggregation (MSA), which utilizes
multi-scale features from different layers of the feature extractor, has
recently been introduced and shows superior performance for variable-duration
utterances. To increase the robustness dealing with utterances of arbitrary
duration, this paper improves the MSA by using a feature pyramid module. The
module enhances speaker-discriminative information of features from multiple
layers via a top-down pathway and lateral connections. We extract speaker
embeddings using the enhanced features that contain rich speaker information
with different time scales. Experiments on the VoxCeleb dataset show that the
proposed module improves previous MSA methods with a smaller number of
parameters. It also achieves better performance than state-of-the-art
approaches for both short and long utterances.Comment: Accepted to Interspeech 202
Informal proof, formal proof, formalism
Increases in the use of automated theorem-provers have renewed focus on the relationship between the informal proofs normally found in mathematical research and fully formalised derivations. Whereas some claim that any correct proof will be underwritten by a fully formal proof, sceptics demur. In this paper I look at the relevance of these issues for formalism, construed as an anti-platonistic metaphysical doctrine. I argue that there are strong reasons to doubt that all proofs are fully formalisable, if formal proofs are required to be finitary, but that, on a proper view of the way in which formal proofs idealise actual practice, this restriction is unjustified and formalism is not threatened
The Experience of Security in Mathematics
In this paper, we report some findings from an investigation of a topic related to affect and mathematics which is not well-represented in the literature. For some mathematicians, mathematics itself is a source of security in an uncertain world, and we investigated this feeling and experience in the case of 19 adult mathematicians working in universities and schools in Greece. The focus reported here is on ways that a relationship with mathematics offers a sense of permanence and stability on the one hand, and an assurance of novelty and progress on the other
Assessing relevance
This paper advances an approach to relevance grounded on patterns of material inference called argumentation schemes, which can account for the reconstruction and the evaluation of relevance relations. In order to account for relevance in different types of dialogical contexts, pursuing also non-cognitive goals, and measuring the scalar strength of relevance, communicative acts are conceived as dialogue moves, whose coherence with the previous ones or the context is represented as the conclusion of steps of material inferences. Such inferences are described using argumentation schemes and are evaluated by considering 1) their defeasibility, and 2) the acceptability of the implicit premises on which they are based. The assessment of both the relevance of an utterance and the strength thereof depends on the evaluation of three interrelated factors: 1) number of inferential steps required; 2) the types of argumentation schemes involved; and 3) the implicit premises required
Bakhtin as a theory of reading
Includes bibliographical references (p. 20
Tracing Linguistic Relations in Winning and Losing Sides of Explicit Opposing Groups
Linguistic relations in oral conversations present how opinions are
constructed and developed in a restricted time. The relations bond ideas,
arguments, thoughts, and feelings, re-shape them during a speech, and finally
build knowledge out of all information provided in the conversation. Speakers
share a common interest to discuss. It is expected that each speaker's reply
includes duplicated forms of words from previous speakers. However, linguistic
adaptation is observed and evolves in a more complex path than just
transferring slightly modified versions of common concepts. A conversation
aiming a benefit at the end shows an emergent cooperation inducing the
adaptation. Not only cooperation, but also competition drives the adaptation or
an opposite scenario and one can capture the dynamic process by tracking how
the concepts are linguistically linked. To uncover salient complex dynamic
events in verbal communications, we attempt to discover self-organized
linguistic relations hidden in a conversation with explicitly stated winners
and losers. We examine open access data of the United States Supreme Court. Our
understanding is crucial in big data research to guide how transition states in
opinion mining and decision-making should be modeled and how this required
knowledge to guide the model should be pinpointed, by filtering large amount of
data.Comment: Full paper, Proceedings of FLAIRS-2017 (30th Florida Artificial
Intelligence Research Society), Special Track, Artificial Intelligence for
Big Social Data Analysi
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