We present the Montreal Forced Aligner (MFA), a new opensource system for speech-text alignment. MFA is an update to the Prosodylab-Aligner, and maintains its key functionality of trainability on new data, as well as incorporating improved architecture (triphone acoustic models and speaker adaptation), and other features. MFA uses Kaldi instead of HTK, allowing MFA to be distributed as a stand-alone package, and to exploit parallel processing for computationally-intensive training and scaling to larger datasets. We evaluate MFA's performance on aligning word and phone boundaries in English conversational and laboratory speech, relative to human-annotated boundaries, focusing on the effects of aligner architecture and training on the data to be aligned. MFA performs well relative to two existing open-source aligners with simpler architecture (Prosodylab-Aligner and FAVE), and both its improved architecture and training on data to be aligned generally result in more accurate boundaries.

Speech datasets from many languages, styles, and sources exist in the world, representing significant potential for scientific studies of speech-particularly given structural similarities among all speech datasets. However, studies using multiple speech corpora remain difficult in practice, due to corpus size, complexity, and differing formats. We introduce open-source software for unified corpus analysis: integrating speech corpora and querying across them. Corpora are stored in a custom 'polyglot persistence' scheme that combines three sub-databases mirroring different data types: a Neo4j graph database to represent temporal annotation graph structure, and SQL and InfluxDB databases to represent meta-and acoustic data. This scheme abstracts away from the idiosyncratic formats of different speech corpora, while mirroring the structure of different data types improves speed and scalability. A Python API and a GUI both allow for: enriching the database with positional, hierarchical, temporal, and signal measures (e.g. utterance boundaries, f0) that are useful for linguistic analysis; querying the database using a simple query language; and exporting query results to standard formats for further analysis. We describe the software, summarize two case studies using it to examine effects on pitch and duration across languages, and outline planned future development.

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Idioms are unlike other phrases in two important ways. First, the words in an idiom have unconventional meanings. Second, the unconventional meaning of words in an idiom are contingent on the presence of the other words in the idiom. Linguistic theories disagree about whether these two properties depend on one another, as well as whether special theoretical machinery is needed to accommodate idioms. We define two measures that correspond to these two properties, and we show that idioms fall at the expected intersection of the two dimensions, but that the dimensions themselves are not correlated. Our results suggest that idioms are no more anomalous than other types of phrases, and that introducing special machinery to handle idioms may not be warranted.