how to get learning resources for FluentAnyEnglish
2026-08-09  / project  / fal

FluentAnyLang practices listening and speaking sentence by sentence. For that it needs two things you bring yourself: media (audio or video) and timed subtitles (.srt / .lrc). This note is a short map of where those pieces usually come from.

App overview: docs · GitHub

Find media

Almost any spoken content works — podcasts, lectures, dramas, songs, conference talks, or something you recorded yourself. Prefer clear speech and a length you will actually finish; you can always split a long file into clips later.

Common places people start:

Source Notes
Your own files Voice memos, class recordings, exported meeting audio
Podcasts / courses e.g. EnglishPod dialog tracks; many ship MP3s you already own
YouTube / open talks TED, conference keynotes, public lectures (download with tools you trust, respect the license)
Shows you own Rips or offline copies from a legal purchase; pair with matching subtitle files below

FluentAnyLang does not ship curriculum media. Whatever you can play locally, you can import.

Find subtitles

Subtitles drive jump / loop. Untimed text alone is not enough — you still need cues aligned to the audio.

Ready-made files

  1. Bundled with the media — courses and some podcast packs already include .srt / .lrc.
  2. Platform captions — export or download official captions when the host allows it, then check timing against the file you actually play.
  3. subtitle-library — an open collection of time-aligned learning subtitles (no media inside the repo). Each theme README explains how to obtain the matching audio/video and how to name files so players auto-load them. Current themes include EnglishPod dialogs and Downton Abbey clips. Details: docs. Pull requests for new themes or fixes are welcome — see the repo CONTEXT.md.

Generate or re-align

When nothing fits your media, or an existing subtitle drifts:

  • Media only → generate a timed .srt from speech
  • Script (.txt) → keep your wording, force-align times to the audio
  • Existing .srt / .lrc → refine each cue against the waveform (not only a single global offset)

sub-align covers those cases with WhisperX forced alignment. Install and usage: docs. Issues and improvements on GitHub are appreciated.

Import and practice

  1. Put media and subtitle side by side (same basename helps many players, including FluentAnyLang's import flow).
  2. Open the app, import the pair, and start listening or speaking practice.
  3. Optional: use ambient noise packs if you train with anti-noise listen.

That is the whole loop — pick content you care about, attach timed lines, and practice on-device.