$$\     $$\                                             
  $$ |    $$ |                                            
$$$$$$\ $$$$$$\    $$$$$$$\  $$$$$$\  $$$$$$$\ $$\    $$\ 
\_$$  _|\_$$  _|  $$  _____|$$  __$$\ $$  __$$\\$$\  $$  |
  $$ |    $$ |    $$ /      $$ /  $$ |$$ |  $$ |\$$\$$  / 
  $$ |$$\ $$ |$$\ $$ |      $$ |  $$ |$$ |  $$ | \$$$  /  
  \$$$$  |\$$$$  |\$$$$$$$\ \$$$$$$  |$$ |  $$ |  \$  /   
   \____/  \____/  \_______| \______/ \__|  \__|   \_/    

ttconv is a library and command line application written in pure Python for converting between timed text formats used in the presentations of captions, subtitles, karaoke, etc.

TTML / IMSC ---                                       --- IMSC / TTML
                \                                   /
SCC / CEA 608 ------- 0 or more document filters --------- WebVTT
                /        [ Canonical Model ]        \
EBU STL -------                                       --- SRT
              /
SRT ---------
            /
WebVTT ----

ttconv works by mapping the input document, whatever its format, into an internal canonical model, which is then optionally transformed by document filters, and finally mapped to the format of the output document is derived. The canonical model closely follows the TTML 2 data model, as constrained by the IMSC 1.1 Text Profile specification.

https://ttconv.sandflow.com/

ttconv currently supports the following input and output formats. Additional input and output formats are planned, and suggestions/contributions are welcome.

• CEA 608/.scc
• IMSC 1.1 Text Profile/.ttml
• EBU STL
• SubRip/.srt
• WebVTT

• SubRip/.srt
• IMSC 1.1 Text Profile/.ttml
• WebVTT

To install the latest version of ttconv, including pre-releases:

pip install --pre ttconv

tt convert -i <input .scc file> -o <output .ttml file>

tt convert [-h] -i INPUT -o OUTPUT [--itype ITYPE] [--otype OTYPE] [--config CONFIG] [--config_file CONFIG_FILE]

• --itype: TTML | SCC | STL | SRT (extrapolated from the filename, if omitted)
• --otype: TTML | SRT | VTT (extrapolated from the filename, if omitted)
• --filter: specifies by name a filter to be applied to the content
• --config and --config_file: JSON dictionary where each property specifies (optional) configuration parameters for readers, writers and filters.

Example:

tt convert -i <.scc file> -o <.ttml file> --itype SCC --otype TTML --filter lcd --config '{"general": {"progress_bar":false, "log_level":"WARN"}, "lcd": {"bg_color": "transparent", "color": "#FF0000"}}'

"progress_bar": true | false

A progress bar is displayed if progress_bar is true and log_level is "INFO".

Default: true

"log_level": "INFO" | "WARN" | "ERROR"

Logging verbosity

Default: "INFO"

"document_lang": <RFC 5646 language tag>

Overrides the top-level language of the input document.

Example: "document_lang": "es-419"

Default: None

"time_format": "frames" | "clock_time" | "clock_time_with_frames"

Specifies whether the TTML time expressions are in frames (f), HH:MM:SS.mmm or HH:MM:SS:FF

Default: "frames" if "fps" is specified, "clock_time" otherwise

"fps": "<num>/<denom>"

Specifies the ttp:frameRate and ttp:frameRateMultiplier of the output document.

Required when time_format is frames or clock_time_with_frames. No effect otherwise.

Example:

--config '{"general": {"progress_bar":false, "log_level":"WARN"}, "imsc_writer": {"time_format":"clock_time_with_frames", "fps": "25/1"}}'

"disable_fill_line_gap" : true | false

true means that the STL reader does not fill gaps between lines

Default: false

"disable_line_padding" : true | false

true means that the STL reader does not add padding at the begining/end of lines

Default: false

"program_start_tc" : "TCP" | "HH:MM:SS:FF"

Specifies a starting offset, either the TCP field of the GSI block or a user-specified timecode

Default: "00:00:00:00"

"font_stack" : [<font-families>](https://www.w3.org/TR/ttml2/#style-value-font-families)

Overrides the font stack

Default: "Verdana, Arial, Tiresias, sansSerif"

"max_row_count" : "MNR" | integer

Specifies a maximum number of rows for open subtitles, either the MNR field of the GSI block or a user-specified value

Default: 23

"text_formatting" : true | false

false means that the SRT writer does not output any text formatting tags

Default: true

"line_position" : true | false

true means that the VTT writer outputs line and line alignment cue settings

Default: false

"text_align" : true | false

true means that the VTT writer outputs text alignment cue settings

Default: false

"cue_id" : true | false

true means that the VTT writer outputs cue identifiers

Default: true

"text_align" : "auto" | "left" | "center" | "right"

Specifies the text alignment. "auto" means the reader will use heuristics to determine text alignment.

Default: "auto"

The LCD filter merges regions and removes all text formatting with the exception of color and text alignment.

"safe_area" : <integer between 0 and 30>

Specifies the safe area (as a percentage of the height and width of the root container)

Default: 10

"color" : <TTML color> | null

If not null, overrides text color. The syntax of TTML color is specified at https://www.w3.org/TR/ttml2/#style-value-color.

Default: null

Examples: "#FFFFFF" (white), "white"

"bg_color" : <TTML color>

If not null, overrides the background color. The syntax of TTML color is specified at https://www.w3.org/TR/ttml2/#style-value-color.

Default: null

Examples: "#FF0000" (red), "transparent", "black"

"preserve_text_align" : true | false

If true, text alignment is preserved, otherwise text is centered.

Default: false

The overall architecture of the library is as follows:

• Reader modules validate and convert input files into instances of the canonical model (see ttconv.imsc.reader.to_model() for example);
• Filter modules transform instances of the canonical data model, e.g. all text styling and positioning might be removed from an instance of the canonical model to match the limited capabilities of downstream devices; and
• Writer modules convert instances of the canonical data model into output files.

Processing shared across multiple reader and writer modules is factored out in common modules whenever possible. For example, several output formats require an instance of the canonical data model to be transformed into a sequence of discrete temporal snapshots – a process called ISD generation.

The library uses the Python logging module to report non-fatal events.

Unit tests illustrate the use of the library, e.g. ReaderWriterTest.test_imsc_1_test_suite at src/test/python/test_imsc_writer.py.

Detailed documentation including reference documents is under doc.

• python >= 3.7

The project uses pipenv to manage dependencies.

• pylint
• coverage

• run pipenv install --dev
• set the PYTHONPATH environment variable to src/main/python, e.g. export PYTHONPATH=src/main/python
• pipenv run can then be used

docker build --rm -f Dockerfile -t ttconv:latest .
docker run -it --rm ttconv:latest bash

From the root directory of the project:

mkdir build
pipenv install --dev
export PYTHONPATH=src/main/python
python src/main/python/ttconv/tt.py convert -i src/test/resources/scc/mix-rows-roll-up.scc -o build/mix-rows-roll-up.ttml

Unit test code coverage is provided by the script at scripts/coverage.sh

Automated testing is provided by the script at scripts/ci.sh

Run PYTHONPATH=src/main/python ./scripts/ci.sh

See .github/workflows/main.yml

Run docker run -it --rm ttconv:latest /bin/sh scripts/ci.sh