Montreal Forced Aligner: Trainable Text-Speech Alignment Using Kaldi
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doi.org/10.21437/interspeech.2017-1386 →Countries where authors are citing Montreal Forced Aligner: Trainable Text-Speech Alignment Using Kaldi
This map shows the geographic impact of Montreal Forced Aligner: Trainable Text-Speech Alignment Using Kaldi. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Montreal Forced Aligner: Trainable Text-Speech Alignment Using Kaldi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Montreal Forced Aligner: Trainable Text-Speech Alignment Using Kaldi more than expected).
Fields of papers citing Montreal Forced Aligner: Trainable Text-Speech Alignment Using Kaldi
This network shows the impact of Montreal Forced Aligner: Trainable Text-Speech Alignment Using Kaldi. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Montreal Forced Aligner: Trainable Text-Speech Alignment Using Kaldi.
About Montreal Forced Aligner: Trainable Text-Speech Alignment Using Kaldi
This paper, published in 2017, received 709 indexed citations . Written by Michael McAuliffe, Michaela Socolof, Michael Wagner and Morgan Sonderegger covering the research area of Artificial Intelligence. It is primarily cited by scholars working on Artificial Intelligence (473 citations), Signal Processing (291 citations), Experimental and Cognitive Psychology (228 citations), Linguistics and Language (93 citations) and Cognitive Neuroscience (64 citations).
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.
This paper is also available at doi.org/10.21437/interspeech.2017-1386.