[Feature request] Add word-level timing metadata and short-utterance guidance for GenAI Speech Recognition

**What's your feature request? Please describe.**

We are evaluating `com.google.mlkit:genai-speech-recognition:1.0.0-alpha1` for a production Android app that performs live, structured voice-command transcription from short utterances in noisy environments.

We would like ML Kit GenAI Speech Recognition to expose richer recognition metadata. The current alpha API appears to expose only `text: String` on `PartialTextResponse` and `FinalTextResponse`. For production use, we need word-level metadata such as:

- token/word text
- start/end offsets
- confidence scores, if available
- alignment/timing data for partial and final results

Without timing/alignment data, apps must synthesize word timing, which is too error-prone for workflows that need to group words into phrases and correlate recognition with VAD/audio events.

We also need documented guidance on the intended audio/session pattern for short utterances, including:

- recommended minimum clip duration
- recommended lead/tail padding
- silence handling
- endpointing behavior
- whether short session-based recognition is supported
- whether long continuous streams are the intended usage pattern

**Mobile environment**

Android

ML Kit API/version: `com.google.mlkit:genai-speech-recognition:1.0.0-alpha1`

**Additional context**

Related Issue Tracker feature request: https://issuetracker.google.com/issues/540021698

In our testing with real live-use audio replayed through `AudioSource.fromPfd()`:

- A single long speech-only stream continued receiving audio for the full stream but recognized only about 48 words from a 1,234-word expected transcript.
- Separate VAD-derived clips as individual recognizer sessions improved coverage slightly to about 119 words, but most clips returned `ERROR_TYPE_NO_SPEECH_DETECTED`.

This appears related to existing reports about `AudioSource.fromPfd()` sensitivity to silence/endpointing, but this request is broader: richer response metadata plus guidance on the intended usage pattern for short utterance recognition.

No repository file, test, or entry point is named. Start by reviewing the com.google.mlkit:genai-speech-recognition:1.0.0-alpha1 API and the related Issue Tracker request; completion would require supported word-level metadata and documented guidance for short-utterance audio sessions.

Written by the indexing model from the issue text.