Janne Pylkkönen - researchr alias

researchr

You are not signed in
Sign in
Sign up

Viewing Publication 1 - 18 from 18

2021

Fast Text-Only Domain Adaptation of RNN-Transducer Prediction NetworkJanne Pylkkönen, Antti Ukkonen, Juho Kilpikoski, Samu Tamminen, Hannes Heikinheimo. interspeech 2021: 1882-1886 [doi]

2016

Active and Semi-Supervised Learning in ASR: Benefits on the Acoustic and Language ModelsThomas Drugman, Janne Pylkkönen, Reinhard Kneser. interspeech 2016: 2318-2322 [doi]

Optimizing Speech Recognition Evaluation Using Stratified SamplingJanne Pylkkönen, Thomas Drugman, Max Bisani. interspeech 2016: 3106-3110 [doi]

2013

Towards Efficient and Robust Automatic Speech Recognition: Decoding Techniques and Discriminative Training ; Kohti tehokasta ja häiriöitä sietävää automaattista puheentunnistusta: tekniikoita dekoodaukseen ja diskriminatiiviseen opetukseenJanne Pylkkönen. PhD thesis, Aalto University, Helsinki, Finland, 2013. [doi]

2012

Analysis of Extended Baum-Welch and Constrained Optimization for Discriminative Training of HMMsJanne Pylkkönen, Mikko Kurimo. taslp, 20(9):2409-2419, 2012. [doi]

Optimization-Based Control for the Extended Baum-Welch AlgorithmJanne Pylkkönen, Mikko Kurimo. interspeech 2012: 1808-1811 [doi]

Improving Discriminative Training for Robust Acoustic Models in Large Vocabulary Continuous Speech RecognitionJanne Pylkkönen, Mikko Kurimo. interspeech 2012: 1211-1214 [doi]

2009

Importance of High-Order N-Gram Models in Morph-Based Speech RecognitionTeemu Hirsimäki, Janne Pylkkönen, Mikko Kurimo. taslp, 17(4):724-732, 2009. [doi]

Investigations on discriminative training in large scale acoustic model estimationJanne Pylkkönen. interspeech 2009: 220-223 [doi]

2007

2006

2005

New pruning criteria for efficient decodingJanne Pylkkönen. interspeech 2005: 581-584 [doi]

2004

Duration modeling techniques for continuous speech recognitionJanne Pylkkönen, Mikko Kurimo. interspeech 2004: 385-388 [doi]

Sign in or sign up to see more results.

runs on WebDSL