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Found 11 papers, 4 papers with code
Improved POS tagging for spontaneous, clinical speech using data augmentation
This paper addresses the problem of improving POS tagging of transcripts of speech from clinical populations.
A Part-of-Speech Tagger for Yiddish
We describe the construction and evaluation of a part-of-speech tagger for Yiddish.
Penn-Helsinki Parsed Corpus of Early Modern English: First Parsing Results and Analysis
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 syntactic change.
Automatic recognition of suprasegmentals in speech
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 recognition.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
The Third DIHARD Diarization Challenge
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 conditions, and conversational domain.
Probing Acoustic Representations for Phonetic Properties
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 limited.
CHiME-6 Challenge:Tackling Multispeaker Speech Recognition for Unsegmented Recordings
Following the success of the 1st, 2nd, 3rd, 4th and 5th CHiME challenges we organize the 6th CHiME Speech Separation and Recognition Challenge (CHiME-6).
Parsing Early Modern English for Linguistic Search
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.
The Second DIHARD Diarization Challenge: Dataset, task, and baselines
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 in recording equipment, noise conditions, and conversational domain.
