5 citations · 5 across the 1 of their papers we have counts for
6 papers
This is the way: designing and compiling LEPISZCZE, a comprehensive NLP benchmark for Polish
Łukasz Augustyniak, Kamil Tagowski, Albert Sawczyn +9
The availability of compute and data to train larger and larger language models increases the demand for robust methods of benchmarking the true progress of LM training. Recent yea…
WER we are and WER we think we are
Piotr Szymański, Piotr Żelasko, Mikolaj Morzy +6
Natural language processing of conversational speech requires the availability of high-quality transcripts. In this paper, we express our skepticism towards the recent reports of v…
Punctuation Prediction in Spontaneous Conversations: Can We Mitigate ASR Errors with Retrofitted Word Embeddings?
Łukasz Augustyniak, Piotr Szymanski, Mikołaj Morzy +5
Automatic Speech Recognition (ASR) systems introduce word errors, which often confuse punctuation prediction models, turning punctuation restoration into a challenging task. These…
Avaya Conversational Intelligence: A Real-Time System for Spoken Language Understanding in Human-Human Call Center Conversations
Jan Mizgajski, Adrian Szymczak, Robert Głowski +14
Avaya Conversational Intelligence(ACI) is an end-to-end, cloud-based solution for real-time Spoken Language Understanding for call centers. It combines large vocabulary, real-time…
Towards Better Understanding of Spontaneous Conversations: Overcoming Automatic Speech Recognition Errors With Intent Recognition
Piotr Żelasko, Jan Mizgajski, Mikołaj Morzy +4
In this paper, we present a method for correcting automatic speech recognition (ASR) errors using a finite state transducer (FST) intent recognition framework. Intent recognition i…
Punctuation Prediction Model for Conversational Speech
Piotr Żelasko, Piotr Szymański, Jan Mizgajski +3
An ASR system usually does not predict any punctuation or capitalization. Lack of punctuation causes problems in result presentation and confuses both the human reader andoff-the-s…