diff --git a/evals/stt/README.md b/evals/stt/README.md
new file mode 100644
index 0000000..b176039
--- /dev/null
+++ b/evals/stt/README.md
@@ -0,0 +1,100 @@
+# STT Evaluation Benchmark
+
+Benchmark for comparing Speech-to-Text providers with focus on:
+- **Speaker diarization** - identifying who said what
+- **Keyterm boosting** - improving recognition of specific terms (Deepgram)
+
+## Providers
+
+| Provider | Diarization | Keyterm Boost | Notes |
+|----------|-------------|---------------|-------|
+| Deepgram | Yes | Yes | `diarize=true`, `keyterm` param |
+| Speechmatics | Yes | No | `diarization: "speaker"` config |
+
+## Setup
+
+```bash
+# Install dependencies (httpx is required)
+pip install httpx
+
+# Set API keys
+export DEEPGRAM_API_KEY="your-key"
+export SPEECHMATICS_API_KEY="your-key"
+```
+
+## Usage
+
+Run from the project root directory:
+
+```bash
+# Test both providers with diarization
+python -m evals.stt.benchmark audio/multi_speaker.m4a --diarize
+
+# Test only Deepgram
+python -m evals.stt.benchmark audio/multi_speaker.m4a --diarize --providers deepgram
+
+# Test with keyterm boosting (Deepgram only)
+python -m evals.stt.benchmark audio/multi_speaker.m4a --diarize --keyterms "Dograh" "Pipecat"
+
+# Show word-level timings
+python -m evals.stt.benchmark audio/multi_speaker.m4a --diarize --show-words
+
+# Save results to JSON
+python -m evals.stt.benchmark audio/multi_speaker.m4a --diarize --save
+```
+
+## CLI Options
+
+| Option | Description |
+|--------|-------------|
+| `audio_file` | Path to audio file (relative to evals/stt/ or absolute) |
+| `--providers` | Providers to test: `deepgram`, `speechmatics` (default: both) |
+| `--diarize` | Enable speaker diarization |
+| `--keyterms` | Keywords to boost (Deepgram only) |
+| `--language` | Language code (default: en) |
+| `--show-words` | Show individual word timings |
+| `--save` | Save results to JSON in `results/` |
+
+## Directory Structure
+
+```
+evals/stt/
+├── audio/              # Audio test files
+│   └── multi_speaker.m4a
+├── results/            # Saved benchmark results (JSON)
+├── providers/          # STT provider implementations
+│   ├── base.py         # Base classes
+│   ├── deepgram_provider.py
+│   └── speechmatics_provider.py
+├── benchmark.py        # Main runner script
+└── README.md
+```
+
+## Output Example
+
+```
+Provider: DEEPGRAM
+Duration: 45.32s
+Speakers detected: 2 - ['0', '1']
+
+Transcript:
+Hello, welcome to the demo...
+
+--- Speaker Segments ---
+[0.0s] Speaker 0: Hello, welcome to the demo.
+[2.5s] Speaker 1: Thanks for having me.
+...
+```
+
+## Adding New Providers
+
+1. Create a new file in `providers/` (e.g., `whisper_provider.py`)
+2. Implement the `STTProvider` abstract class
+3. Add to `providers/__init__.py`
+4. Add to `benchmark.py` provider choices
+
+## API Documentation
+
+- Deepgram Diarization: https://developers.deepgram.com/docs/diarization
+- Deepgram Keyterms: https://developers.deepgram.com/docs/keyterm
+- Speechmatics Diarization: https://docs.speechmatics.com/features/diarization
diff --git a/evals/stt/__init__.py b/evals/stt/__init__.py
new file mode 100644
index 0000000..8c12ae8
--- /dev/null
+++ b/evals/stt/__init__.py
@@ -0,0 +1 @@
+# STT Evaluation Benchmark
diff --git a/evals/stt/audio/multi_speaker.m4a b/evals/stt/audio/multi_speaker.m4a
new file mode 100644
index 0000000..d1ab1f5
Binary files /dev/null and b/evals/stt/audio/multi_speaker.m4a differ
diff --git a/evals/stt/benchmark.py b/evals/stt/benchmark.py
new file mode 100644
index 0000000..c1b5fed
--- /dev/null
+++ b/evals/stt/benchmark.py
@@ -0,0 +1,230 @@
+#!/usr/bin/env python3
+"""STT Benchmark Runner.
+
+Compare speech-to-text transcription across providers with focus on:
+- Speaker diarization accuracy
+- Keyword/keyterm recognition
+- Transcription quality
+
+Usage:
+    python -m evals.stt.benchmark audio/multi_speaker.m4a --diarize
+    python -m evals.stt.benchmark audio/multi_speaker.m4a --diarize --providers deepgram
+    python -m evals.stt.benchmark audio/multi_speaker.m4a --diarize --keyterms "Dograh" "Pipecat"
+"""
+
+import argparse
+import asyncio
+import json
+import sys
+from datetime import datetime
+from pathlib import Path
+from typing import Any
+
+from evals.stt.providers import DeepgramProvider, SpeechmaticsProvider, STTProvider, TranscriptionResult
+
+
+def get_provider(name: str) -> STTProvider:
+    """Get provider instance by name."""
+    providers = {
+        "deepgram": DeepgramProvider,
+        "speechmatics": SpeechmaticsProvider,
+    }
+    if name not in providers:
+        raise ValueError(f"Unknown provider: {name}. Available: {list(providers.keys())}")
+    return providers[name]()
+
+
+async def run_transcription(
+    provider: STTProvider,
+    audio_path: Path,
+    diarize: bool = False,
+    keyterms: list[str] | None = None,
+    **kwargs: Any,
+) -> TranscriptionResult:
+    """Run transcription with a provider."""
+    print(f"\n{'='*60}")
+    print(f"Provider: {provider.name.upper()}")
+    print(f"{'='*60}")
+
+    try:
+        result = await provider.transcribe(
+            audio_path,
+            diarize=diarize,
+            keyterms=keyterms,
+            **kwargs,
+        )
+        return result
+    except Exception as e:
+        print(f"Error with {provider.name}: {e}")
+        raise
+
+
+def print_result(result: TranscriptionResult, show_words: bool = False) -> None:
+    """Print transcription result."""
+    print(f"\nDuration: {result.duration:.2f}s")
+    print(f"Speakers detected: {len(result.speakers)} - {result.speakers}")
+    print(f"\nTranscript:\n{result.transcript}")
+
+    if result.speakers:
+        print(f"\n--- Speaker Segments ---")
+        for segment in result.get_speaker_segments():
+            speaker = segment["speaker"] or "?"
+            text = segment["text"]
+            start = segment["start"]
+            print(f"[{start:.1f}s] Speaker {speaker}: {text}")
+
+    if show_words:
+        print(f"\n--- Words ---")
+        for word in result.words[:50]:  # First 50 words
+            speaker_info = f" (S{word.speaker})" if word.speaker else ""
+            print(f"  {word.start:.2f}s: {word.word}{speaker_info} [{word.confidence:.2f}]")
+        if len(result.words) > 50:
+            print(f"  ... and {len(result.words) - 50} more words")
+
+
+def save_results(
+    results: list[TranscriptionResult],
+    output_dir: Path,
+    audio_name: str,
+) -> Path:
+    """Save results to JSON file."""
+    output_dir.mkdir(parents=True, exist_ok=True)
+    timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
+    output_file = output_dir / f"{audio_name}_{timestamp}.json"
+
+    output_data = {
+        "timestamp": timestamp,
+        "audio_file": audio_name,
+        "results": [r.to_dict() for r in results],
+    }
+
+    with open(output_file, "w") as f:
+        json.dump(output_data, f, indent=2)
+
+    print(f"\nResults saved to: {output_file}")
+    return output_file
+
+
+def compare_results(results: list[TranscriptionResult]) -> None:
+    """Compare results across providers."""
+    if len(results) < 2:
+        return
+
+    print(f"\n{'='*60}")
+    print("COMPARISON SUMMARY")
+    print(f"{'='*60}")
+
+    print(f"\n{'Provider':<15} {'Duration':<10} {'Speakers':<10} {'Words':<10}")
+    print("-" * 45)
+    for r in results:
+        print(f"{r.provider:<15} {r.duration:<10.2f} {len(r.speakers):<10} {len(r.words):<10}")
+
+    # Compare speaker counts
+    speaker_counts = {r.provider: len(r.speakers) for r in results}
+    if len(set(speaker_counts.values())) > 1:
+        print(f"\nNote: Providers detected different speaker counts: {speaker_counts}")
+
+
+async def main() -> int:
+    parser = argparse.ArgumentParser(
+        description="STT Benchmark - Compare transcription providers",
+        formatter_class=argparse.RawDescriptionHelpFormatter,
+        epilog="""
+Examples:
+  python -m evals.stt.benchmark audio/multi_speaker.m4a --diarize
+  python -m evals.stt.benchmark audio/multi_speaker.m4a --diarize --providers deepgram
+  python -m evals.stt.benchmark audio/multi_speaker.m4a --keyterms "Dograh" "API"
+        """,
+    )
+    parser.add_argument(
+        "audio_file",
+        type=str,
+        help="Path to audio file (relative to evals/stt/ or absolute)",
+    )
+    parser.add_argument(
+        "--providers",
+        nargs="+",
+        default=["deepgram", "speechmatics"],
+        choices=["deepgram", "speechmatics"],
+        help="Providers to test (default: all)",
+    )
+    parser.add_argument(
+        "--diarize",
+        action="store_true",
+        help="Enable speaker diarization",
+    )
+    parser.add_argument(
+        "--keyterms",
+        nargs="+",
+        help="Keywords to boost (Deepgram only)",
+    )
+    parser.add_argument(
+        "--language",
+        default="en",
+        help="Language code (default: en)",
+    )
+    parser.add_argument(
+        "--show-words",
+        action="store_true",
+        help="Show individual word timings",
+    )
+    parser.add_argument(
+        "--save",
+        action="store_true",
+        help="Save results to JSON file",
+    )
+    parser.add_argument(
+        "--output-dir",
+        type=str,
+        default="results",
+        help="Output directory for results (default: results)",
+    )
+
+    args = parser.parse_args()
+
+    # Resolve audio path
+    script_dir = Path(__file__).parent
+    audio_path = Path(args.audio_file)
+    if not audio_path.is_absolute():
+        audio_path = script_dir / audio_path
+
+    if not audio_path.exists():
+        print(f"Error: Audio file not found: {audio_path}")
+        return 1
+
+    print(f"Audio file: {audio_path}")
+    print(f"Providers: {args.providers}")
+    print(f"Diarization: {args.diarize}")
+    if args.keyterms:
+        print(f"Keyterms: {args.keyterms}")
+
+    results: list[TranscriptionResult] = []
+
+    for provider_name in args.providers:
+        try:
+            provider = get_provider(provider_name)
+            result = await run_transcription(
+                provider,
+                audio_path,
+                diarize=args.diarize,
+                keyterms=args.keyterms,
+                language=args.language,
+            )
+            print_result(result, show_words=args.show_words)
+            results.append(result)
+        except Exception as e:
+            print(f"\nFailed to run {provider_name}: {e}")
+            continue
+
+    if len(results) > 1:
+        compare_results(results)
+
+    if args.save and results:
+        output_dir = script_dir / args.output_dir
+        save_results(results, output_dir, audio_path.stem)
+
+    return 0
+
+
+if __name__ == "__main__":
+    sys.exit(asyncio.run(main()))
diff --git a/evals/stt/providers/__init__.py b/evals/stt/providers/__init__.py
new file mode 100644
index 0000000..d73a2b8
--- /dev/null
+++ b/evals/stt/providers/__init__.py
@@ -0,0 +1,11 @@
+from .base import STTProvider, TranscriptionResult, Word
+from .deepgram_provider import DeepgramProvider
+from .speechmatics_provider import SpeechmaticsProvider
+
+__all__ = [
+    "STTProvider",
+    "TranscriptionResult",
+    "Word",
+    "DeepgramProvider",
+    "SpeechmaticsProvider",
+]
diff --git a/evals/stt/providers/base.py b/evals/stt/providers/base.py
new file mode 100644
index 0000000..cdb4af9
--- /dev/null
+++ b/evals/stt/providers/base.py
@@ -0,0 +1,123 @@
+"""Base classes for STT providers."""
+
+from abc import ABC, abstractmethod
+from dataclasses import dataclass, field
+from pathlib import Path
+from typing import Any
+
+
+@dataclass
+class Word:
+    """Represents a transcribed word with metadata."""
+
+    word: str
+    start: float
+    end: float
+    confidence: float
+    speaker: str | None = None
+    speaker_confidence: float | None = None
+
+    def to_dict(self) -> dict[str, Any]:
+        return {
+            "word": self.word,
+            "start": self.start,
+            "end": self.end,
+            "confidence": self.confidence,
+            "speaker": self.speaker,
+            "speaker_confidence": self.speaker_confidence,
+        }
+
+
+@dataclass
+class TranscriptionResult:
+    """Result from STT transcription."""
+
+    provider: str
+    transcript: str
+    words: list[Word]
+    speakers: list[str]
+    duration: float
+    raw_response: dict[str, Any] = field(default_factory=dict)
+    params: dict[str, Any] = field(default_factory=dict)
+
+    def to_dict(self) -> dict[str, Any]:
+        return {
+            "provider": self.provider,
+            "transcript": self.transcript,
+            "words": [w.to_dict() for w in self.words],
+            "speakers": self.speakers,
+            "duration": self.duration,
+            "params": self.params,
+        }
+
+    def get_speaker_segments(self) -> list[dict[str, Any]]:
+        """Get transcript segmented by speaker."""
+        if not self.words:
+            return []
+
+        segments = []
+        current_speaker = None
+        current_text = []
+        segment_start = 0.0
+
+        for word in self.words:
+            if word.speaker != current_speaker:
+                if current_text:
+                    segments.append(
+                        {
+                            "speaker": current_speaker,
+                            "text": " ".join(current_text),
+                            "start": segment_start,
+                            "end": self.words[len(segments) - 1].end
+                            if segments
+                            else word.start,
+                        }
+                    )
+                current_speaker = word.speaker
+                current_text = [word.word]
+                segment_start = word.start
+            else:
+                current_text.append(word.word)
+
+        if current_text:
+            segments.append(
+                {
+                    "speaker": current_speaker,
+                    "text": " ".join(current_text),
+                    "start": segment_start,
+                    "end": self.words[-1].end if self.words else 0.0,
+                }
+            )
+
+        return segments
+
+
+class STTProvider(ABC):
+    """Abstract base class for STT providers."""
+
+    @property
+    @abstractmethod
+    def name(self) -> str:
+        """Provider name."""
+        pass
+
+    @abstractmethod
+    async def transcribe(
+        self,
+        audio_path: Path,
+        diarize: bool = False,
+        keyterms: list[str] | None = None,
+        **kwargs: Any,
+    ) -> TranscriptionResult:
+        """Transcribe audio file.
+
+        Args:
+            audio_path: Path to the audio file
+            diarize: Enable speaker diarization
+            keyterms: List of keywords to boost (if supported)
+            **kwargs: Provider-specific parameters
+
+        Returns:
+            TranscriptionResult with transcript and metadata
+        """
+        pass
diff --git a/evals/stt/providers/deepgram_provider.py b/evals/stt/providers/deepgram_provider.py
new file mode 100644
index 0000000..c3b1ebd
--- /dev/null
+++ b/evals/stt/providers/deepgram_provider.py
@@ -0,0 +1,174 @@
+"""Deepgram STT provider."""
+
+import os
+from pathlib import Path
+from typing import Any
+
+import httpx
+
+from .base import STTProvider, TranscriptionResult, Word
+
+
+class DeepgramProvider(STTProvider):
+    """Deepgram Speech-to-Text provider.
+
+    API Docs: https://developers.deepgram.com/docs/
+
+    Supports:
+    - Speaker diarization via `diarize=true`
+    - Keyterm boosting via `keyterm` parameter (Nova-3 and Flux models)
+    """
+
+    API_URL = "https://api.deepgram.com/v1/listen"
+
+    def __init__(self, api_key: str | None = None):
+        self.api_key = api_key or os.getenv("DEEPGRAM_API_KEY")
+        if not self.api_key:
+            raise ValueError(
+                "Deepgram API key required. Set DEEPGRAM_API_KEY env var or pass api_key."
+            )
+
+    @property
+    def name(self) -> str:
+        return "deepgram"
+
+    async def transcribe(
+        self,
+        audio_path: Path,
+        diarize: bool = False,
+        keyterms: list[str] | None = None,
+        model: str = "nova-3",
+        language: str = "en",
+        punctuate: bool = True,
+        **kwargs: Any,
+    ) -> TranscriptionResult:
+        """Transcribe audio using Deepgram API.
+
+        Args:
+            audio_path: Path to audio file
+            diarize: Enable speaker diarization
+            keyterms: List of keywords to boost recognition
+            model: Deepgram model (nova-3, nova-2, etc.)
+            language: Language code
+            punctuate: Add punctuation
+            **kwargs: Additional Deepgram parameters
+
+        Returns:
+            TranscriptionResult with transcript and speaker info
+        """
+        params: dict[str, Any] = {
+            "model": model,
+            "language": language,
+            "punctuate": str(punctuate).lower(),
+        }
+
+        if diarize:
+            params["diarize"] = "true"
+
+        # Add keyterms (Deepgram uses repeated keyterm params)
+        if keyterms:
+            params["keyterm"] = keyterms
+
+        # Add any extra kwargs
+        params.update(kwargs)
+
+        # Read audio file
+        audio_data = audio_path.read_bytes()
+
+        # Determine content type
+        suffix = audio_path.suffix.lower()
+        content_types = {
+            ".wav": "audio/wav",
+            ".mp3": "audio/mpeg",
+            ".m4a": "audio/mp4",
+            ".flac": "audio/flac",
+            ".ogg": "audio/ogg",
+            ".webm": "audio/webm",
+        }
+        content_type = content_types.get(suffix, "audio/wav")
+
+        headers = {
+            "Authorization": f"Token {self.api_key}",
+            "Content-Type": content_type,
+        }
+
+        async with httpx.AsyncClient(timeout=120.0) as client:
+            response = await client.post(
+                self.API_URL,
+                params=params,
+                headers=headers,
+                content=audio_data,
+            )
+            response.raise_for_status()
+            data = response.json()
+
+        return self._parse_response(data, params)
+
+    def _parse_response(
+        self, data: dict[str, Any], params: dict[str, Any]
+    ) -> TranscriptionResult:
+        """Parse Deepgram API response."""
+        results = data.get("results", {})
+        channels = results.get("channels", [])
+
+        if not channels:
+            return TranscriptionResult(
+                provider=self.name,
+                transcript="",
+                words=[],
+                speakers=[],
+                duration=0.0,
+                raw_response=data,
+                params=params,
+            )
+
+        # Get first channel, first alternative
+        channel = channels[0]
+        alternatives = channel.get("alternatives", [])
+        if not alternatives:
+            return TranscriptionResult(
+                provider=self.name,
+                transcript="",
+                words=[],
+                speakers=[],
+                duration=0.0,
+                raw_response=data,
+                params=params,
+            )
+
+        alt = alternatives[0]
+        transcript = alt.get("transcript", "")
+
+        # Parse words with speaker info
+        words = []
+        speakers_set: set[str] = set()
+
+        for w in alt.get("words", []):
+            speaker = str(w.get("speaker", "")) if "speaker" in w else None
+            if speaker:
+                speakers_set.add(speaker)
+
+            words.append(
+                Word(
+                    word=w.get("word", ""),
+                    start=w.get("start", 0.0),
+                    end=w.get("end", 0.0),
+                    confidence=w.get("confidence", 0.0),
+                    speaker=speaker,
+                    speaker_confidence=w.get("speaker_confidence"),
+                )
+            )
+
+        # Get duration from metadata
+        metadata = results.get("metadata", {})
+        duration = metadata.get("duration", 0.0)
+
+        return TranscriptionResult(
+            provider=self.name,
+            transcript=transcript,
+            words=words,
+            speakers=sorted(speakers_set),
+            duration=duration,
+            raw_response=data,
+            params=params,
+        )
diff --git a/evals/stt/providers/speechmatics_provider.py b/evals/stt/providers/speechmatics_provider.py
new file mode 100644
index 0000000..8f6ee63
--- /dev/null
+++ b/evals/stt/providers/speechmatics_provider.py
@@ -0,0 +1,210 @@
+"""Speechmatics STT provider."""
+
+import os
+from pathlib import Path
+from typing import Any
+
+import httpx
+
+from .base import STTProvider, TranscriptionResult, Word
+
+
+class SpeechmaticsProvider(STTProvider):
+    """Speechmatics Speech-to-Text provider.
+
+    API Docs: https://docs.speechmatics.com/
+
+    Supports:
+    - Speaker diarization via `diarization: "speaker"` config
+    - Speaker sensitivity tuning
+    """
+
+    # EU and US endpoints available
+    API_URL = "https://asr.api.speechmatics.com/v2/jobs"
+
+    def __init__(self, api_key: str | None = None, region: str = "eu1"):
+        self.api_key = api_key or os.getenv("SPEECHMATICS_API_KEY")
+        if not self.api_key:
+            raise ValueError(
+                "Speechmatics API key required. Set SPEECHMATICS_API_KEY env var or pass api_key."
+            )
+        # Set region-specific endpoint
+        if region == "eu1":
+            self.api_url = "https://eu1.asr.api.speechmatics.com/v2/jobs"
+        else:
+            self.api_url = "https://asr.api.speechmatics.com/v2/jobs"
+
+    @property
+    def name(self) -> str:
+        return "speechmatics"
+
+    async def transcribe(
+        self,
+        audio_path: Path,
+        diarize: bool = False,
+        keyterms: list[str] | None = None,
+        language: str = "en",
+        operating_point: str = "enhanced",
+        speaker_sensitivity: float | None = None,
+        **kwargs: Any,
+    ) -> TranscriptionResult:
+        """Transcribe audio using Speechmatics API.
+
+        Args:
+            audio_path: Path to audio file
+            diarize: Enable speaker diarization
+            keyterms: Not directly supported by Speechmatics (ignored)
+            language: Language code
+            operating_point: "standard" or "enhanced"
+            speaker_sensitivity: 0.0-1.0, higher = more speakers detected
+            **kwargs: Additional config parameters
+
+        Returns:
+            TranscriptionResult with transcript and speaker info
+        """
+        # Build transcription config
+        transcription_config: dict[str, Any] = {
+            "language": language,
+            "operating_point": operating_point,
+        }
+
+        if diarize:
+            transcription_config["diarization"] = "speaker"
+            if speaker_sensitivity is not None:
+                transcription_config["speaker_diarization_config"] = {
+                    "speaker_sensitivity": speaker_sensitivity
+                }
+
+        # Add any extra config
+        transcription_config.update(kwargs)
+
+        config = {
+            "type": "transcription",
+            "transcription_config": transcription_config,
+        }
+
+        # Store params for result
+        params = {
+            "diarize": diarize,
+            "language": language,
+            "operating_point": operating_point,
+            "speaker_sensitivity": speaker_sensitivity,
+        }
+
+        headers = {
+            "Authorization": f"Bearer {self.api_key}",
+        }
+
+        # Create job with multipart form
+        async with httpx.AsyncClient(timeout=300.0) as client:
+            # Submit job
+            with open(audio_path, "rb") as f:
+                files = {
+                    "data_file": (audio_path.name, f, "audio/mpeg"),
+                    "config": (None, str(config).replace("'", '"'), "application/json"),
+                }
+                response = await client.post(
+                    self.api_url,
+                    headers=headers,
+                    files=files,
+                )
+                response.raise_for_status()
+                job_data = response.json()
+
+            job_id = job_data.get("id")
+            if not job_id:
+                raise ValueError(f"No job ID in response: {job_data}")
+
+            # Poll for completion
+            result_data = await self._wait_for_job(client, job_id, headers)
+
+        return self._parse_response(result_data, params)
+
+    async def _wait_for_job(
+        self, client: httpx.AsyncClient, job_id: str, headers: dict[str, str]
+    ) -> dict[str, Any]:
+        """Poll job status until complete."""
+        import asyncio
+
+        job_url = f"{self.api_url}/{job_id}"
+        transcript_url = f"{job_url}/transcript?format=json-v2"
+
+        max_attempts = 120  # 10 minutes with 5s intervals
+        for _ in range(max_attempts):
+            # Check job status
+            status_response = await client.get(job_url, headers=headers)
+            status_response.raise_for_status()
+            status_data = status_response.json()
+
+            job_status = status_data.get("job", {}).get("status")
+
+            if job_status == "done":
+                # Get transcript
+                transcript_response = await client.get(transcript_url, headers=headers)
+                transcript_response.raise_for_status()
+                return transcript_response.json()
+            elif job_status == "rejected":
+                raise ValueError(f"Job rejected: {status_data}")
+            elif job_status == "deleted":
+                raise ValueError(f"Job deleted: {status_data}")
+
+            await asyncio.sleep(5)
+
+        raise TimeoutError(f"Job {job_id} did not complete in time")
+
+    def _parse_response(
+        self, data: dict[str, Any], params: dict[str, Any]
+    ) -> TranscriptionResult:
+        """Parse Speechmatics API response."""
+        results = data.get("results", [])
+
+        words = []
+        speakers_set: set[str] = set()
+        transcript_parts = []
+
+        for item in results:
+            item_type = item.get("type")
+            alternatives = item.get("alternatives", [])
+
+            if not alternatives:
+                continue
+
+            alt = alternatives[0]
+            content = alt.get("content", "")
+            speaker = alt.get("speaker")
+
+            if speaker:
+                speakers_set.add(speaker)
+
+            if item_type == "word":
+                words.append(
+                    Word(
+                        word=content,
+                        start=item.get("start_time", 0.0),
+                        end=item.get("end_time", 0.0),
+                        confidence=alt.get("confidence", 0.0),
+                        speaker=speaker,
+                        speaker_confidence=None,  # Not provided by Speechmatics
+                    )
+                )
+                transcript_parts.append(content)
+            elif item_type == "punctuation":
+                # Append punctuation to last word in transcript
+                if transcript_parts:
+                    transcript_parts[-1] += content
+
+        # Get metadata
+        metadata = data.get("metadata", {})
+        duration = metadata.get("duration", 0.0)
+
+        transcript = " ".join(transcript_parts)
+
+        return TranscriptionResult(
+            provider=self.name,
+            transcript=transcript,
+            words=words,
+            speakers=sorted(speakers_set),
+            duration=duration,
+            raw_response=data,
+            params=params,
+        )