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articubench - An Articulatory Speech Synthesis Benchmark

Project description

A benchmark to evaluate articulatory speech synthesis systems. This benchmark uses the VocalTractLab [1] as its articulatory speech synthesis simulator.

Types of data

  • wave form (acoustics)

  • log-melspectrogramms (acoustics)

  • formant transitions (acoustics)

  • fasttext 300 dim semantic vector for single words (semantics)

  • mid sagital tongue movement contour from ultra sound imaging

  • electromagnetic articulatory (EMA) sensors on tongue tip and tongue body

Languages

  • German

  • English (planned)

  • Mandarin (planned)

Variants

As running the benchmark is computational itensive there are different versions of this benchmark, which require different amounts of articulatory synthesis.

Tiny

The smallest possible benchmark to check that everything works, but with no statistical power.

Small

A small benchmark with some statistical power.

Normal

The standard benchmark, which might take some time to complete.

Corpora

Data used here comes from the following speech corpora:

  • GECO (only phonetic transscription; duration and phone)

  • KEC (EMA data, acoustics)

  • Mozilla Common Voice

  • baba-babi-babu speech rate (ultra sound; acoustics)

Prerequisits

For running the benchmark:

  • python >=3.8

  • praat

For creating the benchmark:

  • mfa (Montreal forced aligner)

  • VTL 2.3 (included in this repository)

License

  • VTL is GPLv3.0+ license

Download files

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Source Distribution

articubench-0.1.0.tar.gz (25.6 kB view hashes)

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