Multi-Dialect Speech Recognition With A Single Sequence-To-Sequence Model

Sequence-to-sequence models provide a simple and elegant solution for building speech recognition systems by folding separate components of a typical system, namely acoustic (AM), pronunciation (PM) and language (LM) models into a single neural network. In this work, we look at one such sequence-to-sequence model, namely listen, attend and spell (LAS), and explore the possibility of training a single model to serve different English dialects, which simplifies the process of training multi-dialect systems without the need for separate AM, PM and LMs for each dialect. We show that simply pooling the data from all dialects into one LAS model falls behind the performance of a model fine-tuned on each dialect. We then look at incorporating dialect-specific information into the model, both by modifying the training targets by inserting the dialect symbol at the end of the original grapheme sequence and also feeding a 1-hot representation of the dialect information into all layers of the model. Experimental results on seven English dialects show that our proposed system is effective in modeling dialect variations within a single LAS model, outperforming a LAS model trained individually on each of the seven dialects by 3.1 ~ 16.5% relative.Comment: submitted to ICASSP 201

Towards dialect-inclusive recognition in a low-resource language: are balanced corpora the answer?

ASR systems are generally built for the spoken 'standard', and their performance declines for non-standard dialects/varieties. This is a problem for a language like Irish, where there is no single spoken standard, but rather three major dialects: Ulster (Ul), Connacht (Co) and Munster (Mu). As a diagnostic to quantify the effect of the speaker's dialect on recognition performance, 12 ASR systems were trained, firstly using baseline dialect-balanced training corpora, and then using modified versions of the baseline corpora, where dialect-specific materials were either subtracted or added. Results indicate that dialect-balanced corpora do not yield a similar performance across the dialects: the Ul dialect consistently underperforms, whereas Mu yields lowest WERs. There is a close relationship between Co and Mu dialects, but one that is not symmetrical. These results will guide future corpus collection and system building strategies to optimise for cross-dialect performance equity.Comment: Accepted to Interspeech 2023, Dubli

Accent rating by native and non-native listeners

This study investigates the influence of listener native language with respect to talker native language on perception of degree of foreign accent in English. Listeners from native English, Finnish, German and Mandarin backgrounds rated the accentedness of native English, Finnish, German and Mandarin talkers producing a controlled set of English sentences. Results indicate that non-native listeners, like native listeners, are able to classify non-native talkers as foreign-accented, and native talkers as unaccented. However, while non-native talkers received higher accentedness ratings than native talkers from all listener groups, non-native listeners judged talkers with non-native accents less harshly than did native English listeners. Similarly, non-native listeners assigned higher degrees of foreign accent to native English talkers than did native English listeners. It seems that non-native listeners give accentedness ratings that are less extreme, or closer to the centre of the rating scale in both directions, than those used by native listeners. Index Terms — Perceptual evaluation, native vs non-native listeners 1

Pioneering Conservation in Alaska

"Designed as a companion to his "Environmental Conflict in Alaska" (2001), which presented the environmental issues of Alaska's statehood period, the newest study by Ross provides an in-depth view of the resource management controversies in Alaska up to statehood in 1958. Ross's chapters on predator control, when wildlife managers offered bounties not just for wolves but for eagles, and another on attempted translocations of ungulates, reveal astounding efforts to manipulate ecosystems. Especially useful is his history of the successful efforts to preserve the Arctic National Wildlife Refuge." CHOICE Magazin

Animals in Our Midst: The Challenges of Co-existing with Animals in the Anthropocene

This Open Access book brings together authoritative voices in animal and environmental ethics, who address the many different facets of changing human-animal relationships in the Anthropocene. As we are living in complex times, the issue of how to establish meaningful relationships with other animals under Anthropocene conditions needs to be approached from a multitude of angles. This book offers the reader insight into the different discussions that exist around the topics of how we should understand animal agency, how we could take animal agency seriously in farms, urban areas and the wild, and what technologies are appropriate and morally desirable to use regarding animals. This book is of interest to both animal studies scholars and environmental ethics scholars, as well as to practitioners working with animals, such as wildlife managers, zookeepers, and conservation biologists

Pioneering Conservation in Alaska

"Designed as a companion to his "Environmental Conflict in Alaska" (2001), which presented the environmental issues of Alaska's statehood period, the newest study by Ross provides an in-depth view of the resource management controversies in Alaska up to statehood in 1958. Ross's chapters on predator control, when wildlife managers offered bounties not just for wolves but for eagles, and another on attempted translocations of ungulates, reveal astounding efforts to manipulate ecosystems. Especially useful is his history of the successful efforts to preserve the Arctic National Wildlife Refuge." CHOICE Magazin