Search Results for author: Leah Findlater

Found 10 papers, 1 papers with code

Latent Phrase Matching for Dysarthric Speech

no code implementations8 Jun 2023 Colin Lea, Dianna Yee, Jaya Narain, Zifang Huang, Lauren Tooley, Jeffrey P. Bigham, Leah Findlater

Many consumer speech recognition systems are not tuned for people with speech disabilities, resulting in poor recognition and user experience, especially for severe speech differences.

speech-recognition Speech Recognition

Nonverbal Sound Detection for Disordered Speech

no code implementations15 Feb 2022 Colin Lea, Zifang Huang, Dhruv Jain, Lauren Tooley, Zeinab Liaghat, Shrinath Thelapurath, Leah Findlater, Jeffrey P. Bigham

Voice assistants have become an essential tool for people with various disabilities because they enable complex phone- or tablet-based interactions without the need for fine-grained motor control, such as with touchscreens.

Event Detection Sound Event Detection

Interactive Refinement of Cross-Lingual Word Embeddings

1 code implementation EMNLP 2020 Michelle Yuan, Mozhi Zhang, Benjamin Van Durme, Leah Findlater, Jordan Boyd-Graber

Cross-lingual word embeddings transfer knowledge between languages: models trained on high-resource languages can predict in low-resource languages.

Active Learning Cross-Lingual Word Embeddings +3

Why Didn't You Listen to Me? Comparing User Control of Human-in-the-Loop Topic Models

no code implementations ACL 2019 Varun Kumar, Alison Smith-Renner, Leah Findlater, Kevin Seppi, Jordan Boyd-Graber

To address the lack of comparative evaluation of Human-in-the-Loop Topic Modeling (HLTM) systems, we implement and evaluate three contrasting HLTM modeling approaches using simulation experiments.

Topic Models

A Differentiable Self-disambiguated Sense Embedding Model via Scaled Gumbel Softmax

no code implementations27 Sep 2018 Fenfei Guo, Mohit Iyyer, Leah Findlater, Jordan Boyd-Graber

We present a differentiable multi-prototype word representation model that disentangles senses of polysemous words and produces meaningful sense-specific embeddings without external resources.

Hard Attention Sentence +1

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