add edge_tts service

manim_voiceover/services/edge.py

@@ -0,0 +1,87 @@
+from manim_voiceover.services.base import SpeechService
+from manim_voiceover.helper import prompt_ask_missing_extras, remove_bookmarks
+from pathlib import Path
+from manim import logger
+from typing import Optional
+
+try:
+    from edge_tts import Communicate
+except ImportError:
+    logger.error(
+        'Missing packages. Run `pip install "manim-voiceover[edge]"` to use EdgeTTSService.'
+    )
+
+
+class EdgeTTSService(SpeechService):
+    """EdgeTTSService class allows you to use Microsoft Edge's online text-to-speech service.
+    This is a wrapper for the edge-tts library.
+    See the `edge-tts documentation <https://pypi.org/project/edge-tts/>`__
+    for more information."""
+
+    def __init__(
+        self,
+        voice: str = "en-US-AriaNeural",
+        rate: str = "+0%",
+        volume: str = "+0%",
+        pitch: str = "+0Hz",
+        proxy: Optional[str] = None,
+        **kwargs
+    ):
+        prompt_ask_missing_extras("edge_tts", "edge_tts", "EdgeTTSService")
+        SpeechService.__init__(self, **kwargs)
+        self.voice = voice
+        self.rate = rate
+        self.volume = volume
+        self.pitch = pitch
+        self.proxy = proxy
+
+    def generate_from_text(
+        self, text: str, cache_dir: str = None, path: str = None, **kwargs
+    ) -> dict:
+        """"""
+        if cache_dir is None:
+            cache_dir = self.cache_dir
+
+        input_text = remove_bookmarks(text)
+        input_data = {
+            "input_text": input_text,
+            "service": "edge",
+            "config": {
+                "voice": self.voice,
+                "rate": self.rate,
+                "volume": self.volume,
+                "pitch": self.pitch,
+            },
+        }
+
+        cached_result = self.get_cached_result(input_data, cache_dir)
+        if cached_result is not None:
+            return cached_result
+
+        if path is None:
+            audio_path = self.get_audio_basename(input_data) + ".mp3"
+        else:
+            audio_path = path
+
+        comm = Communicate(
+            input_text,
+            voice=self.voice,
+            rate=self.rate,
+            volume=self.volume,
+            pitch=self.pitch,
+            proxy=self.proxy,
+        )
+
+        output_file = str(Path(cache_dir) / audio_path)
+        with open(output_file, "wb") as f:
+            for chunk in comm.stream_sync():
+                if chunk["type"] == "audio":
+                    f.write(chunk["data"])
+
+        json_dict = {
+            "input_text": text,
+            "input_data": input_data,
+            "original_audio": audio_path,
+        }
+
+        return json_dict

pyproject.toml

@@ -62,6 +62,7 @@ openai-whisper = { version = "^20230314", optional = true }
 stable-ts = { version ="^2.6.2", optional = true }
 python-slugify = "^8.0.1"
 elevenlabs = {version = "^0.2.27", optional = true}
+edge_tts = { version = "^6.1.12", optional = true }
 
 [tool.poetry.extras]
 azure = ["azure-cognitiveservices-speech"]
@@ -74,6 +75,7 @@ recorder = ["PyAudio", "pynput"]
 translate = ["deepl"]
 elevenlabs = ["elevenlabs"]
 transcribe = ["openai-whisper", "stable-ts"]
+edge = ["edge_tts"]
 all = [
     "azure-cognitiveservices-speech",
     "gTTS",
@@ -86,7 +88,8 @@ all = [
     "deepl",
     "openai-whisper",
     "stable-ts",
-    "elevenlabs"
+    "elevenlabs",
+    "edge"
 ]
 
 [tool.poetry.group.dev.dependencies]