aeneas

fork of aeneas that supports python3.6+.

System Requirements, Supported Platforms and Installation

System Requirements

a reasonably recent machine (recommended 4 GB RAM, 2 GHz 64bit CPU)
Python 3.6+ (Linux, OS X, Windows) or 3.5 or later (Linux, OS X)
FFmpeg
eSpeak
Python packages BeautifulSoup4, lxml, and numpy
Python headers to compile the Python C/C++ extensions (optional but strongly recommended)
A shell supporting UTF-8 (optional but strongly recommended)

Installation

Install Python (3.6+ preferred), FFmpeg, and eSpeak
Make sure the following executables can be called from your shell: espeak, ffmpeg, ffprobe, pip, and python
First install numpy with pip and then aeneas (this order is important):
```
pip install numpy
pip install py3-aeneas
```
To check whether you installed aeneas correctly, run:
```
 python -m aeneas.diagnostics
```

Usage

Run without arguments to get the usage message:

python -m aeneas.tools.execute_task
python -m aeneas.tools.execute_job

You can also get a list of live examples that you can immediately run on your machine thanks to the included files:

python -m aeneas.tools.execute_task --examples
python -m aeneas.tools.execute_task --examples-all

To compute a synchronization map map.json for a pair (audio.mp3, text.txt in plain text format), you can run:
```
python -m aeneas.tools.execute_task \
    audio.mp3 \
    text.txt \
    "task_language=eng|os_task_file_format=json|is_text_type=plain" \
    map.json
```
(The command has been split into lines with \ for visual clarity; in production you can have the entire command on a single line and/or you can use shell variables.)

To compute a synchronization map map.smil for a pair (audio.mp3, page.xhtml containing fragments marked by id attributes like f001), you can run:
```
python -m aeneas.tools.execute_task \
    audio.mp3 \
    page.xhtml \
    "task_language=eng|os_task_file_format=smil|os_task_file_smil_audio_ref=audio.mp3|os_task_file_smil_page_ref=page.xhtml|is_text_type=unparsed|is_text_unparsed_id_regex=f[0-9]+|is_text_unparsed_id_sort=numeric" \
    map.smil
```
As you can see, the third argument (the configuration string) specifies the parameters controlling the I/O formats and the processing options for the task. Consult the documentation for details.
If you have several tasks to process, you can create a job container to batch process them:
```
python -m aeneas.tools.execute_job job.zip output_directory
```
File job.zip should contain a config.txt or config.xml configuration file, providing aeneas with all the information needed to parse the input assets and format the output sync map files. Consult the documentation for details.

The documentation contains a highly suggested tutorial which explains how to use the built-in command line tools.

Documentation and Support

Documentation: http://www.readbeyond.it/aeneas/docs/
Command line tools tutorial: http://www.readbeyond.it/aeneas/docs/clitutorial.html
Library tutorial: http://www.readbeyond.it/aeneas/docs/libtutorial.html
Old, verbose tutorial: A Practical Introduction To The aeneas Package
Mailing list: https://groups.google.com/d/forum/aeneas-forced-alignment
Changelog: http://www.readbeyond.it/aeneas/docs/changelog.html
High level description of how aeneas works: HOWITWORKS
Development history: HISTORY
Testing: TESTING
Benchmark suite: https://readbeyond.github.io/aeneas-benchmark/

Supported Features

Input text files in parsed, plain, subtitles, or unparsed (XML) format
Multilevel input text files in mplain and munparsed (XML) format
Text extraction from XML (e.g., XHTML) files using id and class attributes
Arbitrary text fragment granularity (single word, subphrase, phrase, paragraph, etc.)
Input audio file formats: all those readable by ffmpeg
Output sync map formats: AUD, CSV, EAF, JSON, SMIL, SRT, SSV, SUB, TEXTGRID, TSV, TTML, TXT, VTT, XML
Confirmed working on 38 languages: AFR, ARA, BUL, CAT, CYM, CES, DAN, DEU, ELL, ENG, EPO, EST, FAS, FIN, FRA, GLE, GRC, HRV, HUN, ISL, ITA, JPN, LAT, LAV, LIT, NLD, NOR, RON, RUS, POL, POR, SLK, SPA, SRP, SWA, SWE, TUR, UKR
MFCC and DTW computed via Python C extensions to reduce the processing time
Several built-in TTS engine wrappers: AWS Polly TTS API, eSpeak (default), eSpeak-ng, Festival, MacOS (via say), Nuance TTS API
Default TTS (eSpeak) called via a Python C extension for fast audio synthesis
Possibility of running a custom, user-provided TTS engine Python wrapper (e.g., included example for speect)
Batch processing of multiple audio/text pairs
Download audio from a YouTube video
In multilevel mode, recursive alignment from paragraph to sentence to word level
In multilevel mode, MFCC resolution, MFCC masking, DTW margin, and TTS engine can be specified for each level independently
Robust against misspelled/mispronounced words, local rearrangements of words, background noise/sporadic spikes
Adjustable splitting times, including a max character/second constraint for CC applications
Automated detection of audio head/tail
Output an HTML file for fine tuning the sync map manually (finetuneas project)
Execution parameters tunable at runtime
Code suitable for Web app deployment (e.g., on-demand cloud computing instances)
Extensive test suite including 1,200+ unit/integration/performance tests, that run and must pass before each release

Limitations and Missing Features

Audio should match the text: large portions of spurious text or audio might produce a wrong sync map
Audio is assumed to be spoken: not suitable for song captioning, YMMV for CC applications
No protection against memory swapping: be sure your amount of RAM is adequate for the maximum duration of a single audio file (e.g., 4 GB RAM => max 2h audio; 16 GB RAM => max 10h audio)
Open issues

A Note on Word-Level Alignment

A significant number of users runs aeneas to align audio and text at word-level (i.e., each fragment is a word). Although aeneas was not designed with word-level alignment in mind and the results might be inferior to ASR-based forced aligners for languages with good ASR models, aeneas offers some options to improve the quality of the alignment at word-level:

multilevel text (since v1.5.1),
MFCC nonspeech masking (since v1.7.0, disabled by default),
use better TTS engines, like Festival or AWS/Nuance TTS API (since v1.5.0).

If you use the aeneas.tools.execute_task command line tool, you can add --presets-word switch to enable MFCC nonspeech masking, for example:

$ python -m aeneas.tools.execute_task --example-words --presets-word
$ python -m aeneas.tools.execute_task --example-words-multilevel --presets-word

If you use aeneas as a library, just set the appropriate RuntimeConfiguration parameters. Please see the command line tutorial for details.

License

aeneas is released under the terms of the GNU Affero General Public License Version 3. See the LICENSE file for details.

Licenses for third party code and files included in aeneas can be found in the licenses directory.

No copy rights were harmed in the making of this project.

Supporting and Contributing

Supporting

Would you like supporting the development of aeneas?

I accept sponsorships to

fix bugs,
add new features,
improve the quality and the performance of the code,
port the code to other languages/platforms, and
improve the documentation.

Feel free to get in touch.

Contributing

If you think you found a bug or you have a feature request, please use the GitHub issue tracker to submit it.

If you want to ask a question about using aeneas, your best option consists in sending an email to the mailing list.

Finally, code contributions are welcome! Please refer to the Code Contribution Guide for details about the branch policies and the code style to follow.

Acknowledgments

Many thanks to Nicola Montecchio, who suggested using MFCCs and DTW, and co-developed the first experimental code for aligning audio and text.

Paolo Bertasi, who developed the APIs and Web application for ReadBeyond Sync, helped shaping the structure of this package for its asynchronous usage.

Chris Hubbard prepared the files for packaging aeneas as a Debian/Ubuntu .deb.

Daniel Bair prepared the brew formula for installing aeneas and its dependencies on Mac OS X.

Daniel Bair, Chris Hubbard, and Richard Margetts packaged the installers for Mac OS X and Windows.

Firat Ozdemir contributed the finetuneas HTML/JS code for fine tuning sync maps in the browser.

Willem van der Walt contributed the code snippet to output a sync map in TextGrid format.

Chris Vaughn contributed the MacOS TTS wrapper.

All the mighty GitHub contributors, and the members of the Google Group.

akki2825/aeneas