13 citations · 20 across the 10 of their papers we have counts for
13 papers
Conceptors for Semantic Steering
Ilias Triantafyllopoulos, Young-Min Cho, Ren Tao +6
Activation-based steering provides control of LLM behavior at inference time, but the dominant paradigm reduces each concept to a single direction whose geometry is left largely un…
Evaluating Speech-to-Text Systems with PennSound
Jonathan Wright, Mark Liberman, Neville Ryant +1
A random sample of nearly 10 hours of speech from PennSound, the world's largest online collection of poetry readings and discussions, was used as a benchmark to evaluate several c…
WhiSPA: Semantically and Psychologically Aligned Whisper with Self-Supervised Contrastive and Student-Teacher Learning
Rajath Rao, Adithya Ganesan, Oscar Kjell +10
Current speech encoding pipelines often rely on an additional text-based LM to get robust representations of human communication, even though SotA speech-to-text models often have…
Improved POS tagging for spontaneous, clinical speech using data augmentation
Seth Kulick, Neville Ryant, David J. Irwin +2
This paper addresses the problem of improving POS tagging of transcripts of speech from clinical populations. In contrast to prior work on parsing and POS tagging of transcribed sp…
Inferring Pitch from Coarse Spectral Features
Danni Ma, Neville Ryant, Mark Liberman
Fundamental frequency (F0) has long been treated as the physical definition of "pitch" in phonetic analysis. But there have been many demonstrations that F0 is at best an approxima…
A Part-of-Speech Tagger for Yiddish
Seth Kulick, Neville Ryant, Beatrice Santorini +2
We describe the construction and evaluation of a part-of-speech tagger for Yiddish. This is the first step in a larger project of automatically assigning part-of-speech tags and sy…
Penn-Helsinki Parsed Corpus of Early Modern English: First Parsing Results and Analysis
Seth Kulick, Neville Ryant, Beatrice Santorini
We present the first parsing results on the Penn-Helsinki Parsed Corpus of Early Modern English (PPCEME), a 1.9 million word treebank that is an important resource for research in…
Automatic recognition of suprasegmentals in speech
Jiahong Yuan, Neville Ryant, Xingyu Cai +2
This study reports our efforts to improve automatic recognition of suprasegmentals by fine-tuning wav2vec 2.0 with CTC, a method that has been successful in automatic speech recogn…
The Third DIHARD Diarization Challenge
Neville Ryant, Prachi Singh, Venkat Krishnamohan +6
DIHARD III was the third in a series of speaker diarization challenges intended to improve the robustness of diarization systems to variability in recording equipment, noise condit…
Probing Acoustic Representations for Phonetic Properties
Danni Ma, Neville Ryant, Mark Liberman
Pre-trained acoustic representations such as wav2vec and DeCoAR have attained impressive word error rates (WER) for speech recognition benchmarks, particularly when labeled data is…
Third DIHARD Challenge Evaluation Plan
Neville Ryant, Kenneth Church, Christopher Cieri +3
This paper introduces the third DIHARD challenge, the third in a series of speaker diarization challenges intended to improve the robustness of diarization systems to variation in…
Parsing Early Modern English for Linguistic Search
Seth Kulick, Neville Ryant
We investigate the question of whether advances in NLP over the last few years make it possible to vastly increase the size of data usable for research in historical syntax. This b…
The Second DIHARD Diarization Challenge: Dataset, task, and baselines
Neville Ryant, Kenneth Church, Christopher Cieri +4
This paper introduces the second DIHARD challenge, the second in a series of speaker diarization challenges intended to improve the robustness of diarization systems to variation i…