stamp: adding paper references for model magic numbers

Documenting the "magic numbers" of the `text-to-audio` exmaple,
[original paper](https://arxiv.org/pdf/2306.07691)

Author: kallebysantos

examples/text-to-audio/index.ts

@@ -7,97 +7,105 @@ import { phonemize } from './phonemizer.js';
 
 const { Tensor, RawSession } = Supabase.ai;
 
+/* NOTE: Reference [original paper](https://arxiv.org/pdf/2306.07691#Model%20Training):
+> All datasets were resampled to 24 kHz to match LibriTTS, and the texts
+> were converted into phonemes using phonemizer'
+*/
+const SAMPLE_RATE = 24000; // 24 kHz
+
+/* NOTE: Reference [original paper](https://arxiv.org/pdf/2306.07691#Detailed%20Model%20Architectures):
+> The size of s and c is 256 × 1
+*/
 const STYLE_DIM = 256;
-const SAMPLE_RATE = 24000;
 const MODEL_ID = 'onnx-community/Kokoro-82M-ONNX';
 
 // https://huggingface.co/onnx-community/Kokoro-82M-ONNX#samples
 const ALLOWED_VOICES = [
-  'af_bella',
-  'af_nicole',
-  'af_sarah',
-  'af_sky',
-  'am_adam',
-  'am_michael',
-  'bf_emma',
-  'bf_isabella',
-  'bm_george',
-  'bm_lewis',
+    'af_bella',
+    'af_nicole',
+    'af_sarah',
+    'af_sky',
+    'am_adam',
+    'am_michael',
+    'bf_emma',
+    'bf_isabella',
+    'bm_george',
+    'bm_lewis',
 ];
 
 const session = await RawSession.fromHuggingFace(MODEL_ID);
 
 Deno.serve(async (req) => {
-  const params = new URL(req.url).searchParams;
-  const text = params.get('text') ?? 'Hello from Supabase!';
-  const voice = params.get('voice') ?? 'af_bella';
-
-  if (!ALLOWED_VOICES.includes(voice)) {
-    return Response.json({
-      error: `invalid voice '${voice}'`,
-      must_be_one_of: ALLOWED_VOICES,
-    }, { status: 400 });
-  }
-
-  const tokenizer = await loadTokenizer();
-  const language = voice.at(0); // 'a'merican | 'b'ritish
-  const phonemes = await phonemize(text, language);
-  const { input_ids } = tokenizer(phonemes, {
-    truncation: true,
-  });
-
-  // Select voice style based on number of input tokens
-  const num_tokens = Math.max(
-    input_ids.dims.at(-1) - 2, // Without padding;
-    0,
-  );
-
-  const voiceStyle = await loadVoiceStyle(voice, num_tokens);
-
-  const { waveform } = await session.run({
-    input_ids,
-    style: voiceStyle,
-    speed: new Tensor('float32', [1], [1]),
-  });
-
-  // Do `wave` encoding from rust backend
-  const audio = await waveform.tryEncodeAudio(SAMPLE_RATE);
-
-  return new Response(audio, {
-    headers: {
-      'Content-Type': 'audio/wav',
-    },
-  });
+    const params = new URL(req.url).searchParams;
+    const text = params.get('text') ?? 'Hello from Supabase!';
+    const voice = params.get('voice') ?? 'af_bella';
+
+    if (!ALLOWED_VOICES.includes(voice)) {
+        return Response.json({
+            error: `invalid voice '${voice}'`,
+            must_be_one_of: ALLOWED_VOICES,
+        }, { status: 400 });
+    }
+
+    const tokenizer = await loadTokenizer();
+    const language = voice.at(0); // 'a'merican | 'b'ritish
+    const phonemes = await phonemize(text, language);
+    const { input_ids } = tokenizer(phonemes, {
+        truncation: true,
+    });
+
+    // Select voice style based on number of input tokens
+    const num_tokens = Math.max(
+        input_ids.dims.at(-1) - 2, // Without padding;
+        0,
+    );
+
+    const voiceStyle = await loadVoiceStyle(voice, num_tokens);
+
+    const { waveform } = await session.run({
+        input_ids,
+        style: voiceStyle,
+        speed: new Tensor('float32', [1], [1]),
+    });
+
+    // Do `wave` encoding from rust backend
+    const audio = await waveform.tryEncodeAudio(SAMPLE_RATE);
+
+    return new Response(audio, {
+        headers: {
+            'Content-Type': 'audio/wav',
+        },
+    });
 });
 
 async function loadVoiceStyle(voice: string, num_tokens: number) {
-  const voice_url =
-    `https://huggingface.co/onnx-community/Kokoro-82M-ONNX/resolve/main/voices/${voice}.bin?download=true`;
+    const voice_url =
+        `https://huggingface.co/onnx-community/Kokoro-82M-ONNX/resolve/main/voices/${voice}.bin?download=true`;
 
-  console.log('loading voice:', voice_url);
+    console.log('loading voice:', voice_url);
 
-  const voiceBuffer = await fetch(voice_url).then(async (res) => await res.arrayBuffer());
+    const voiceBuffer = await fetch(voice_url).then(async (res) => await res.arrayBuffer());
 
-  const offset = num_tokens * STYLE_DIM;
-  const voiceData = new Float32Array(voiceBuffer).slice(
-    offset,
-    offset + STYLE_DIM,
-  );
+    const offset = num_tokens * STYLE_DIM;
+    const voiceData = new Float32Array(voiceBuffer).slice(
+        offset,
+        offset + STYLE_DIM,
+    );
 
-  return new Tensor('float32', voiceData, [1, STYLE_DIM]);
+    return new Tensor('float32', voiceData, [1, STYLE_DIM]);
 }
 
 async function loadTokenizer() {
-  // BUG: invalid 'h' not JSON. That's why we need to manually fetch the assets
-  // const tokenizer = await AutoTokenizer.from_pretrained(MODEL_ID);
+    // BUG: invalid 'h' not JSON. That's why we need to manually fetch the assets
+    // const tokenizer = await AutoTokenizer.from_pretrained(MODEL_ID);
 
-  const tokenizerData = await fetch(
-    'https://huggingface.co/onnx-community/Kokoro-82M-ONNX/resolve/main/tokenizer.json?download=true',
-  ).then(async (res) => await res.json());
+    const tokenizerData = await fetch(
+        'https://huggingface.co/onnx-community/Kokoro-82M-ONNX/resolve/main/tokenizer.json?download=true',
+    ).then(async (res) => await res.json());
 
-  const tokenizerConfig = await fetch(
-    'https://huggingface.co/onnx-community/Kokoro-82M-ONNX/resolve/main/tokenizer_config.json?download=true',
-  ).then(async (res) => await res.json());
+    const tokenizerConfig = await fetch(
+        'https://huggingface.co/onnx-community/Kokoro-82M-ONNX/resolve/main/tokenizer_config.json?download=true',
+    ).then(async (res) => await res.json());
 
-  return new PreTrainedTokenizer(tokenizerData, tokenizerConfig);
+    return new PreTrainedTokenizer(tokenizerData, tokenizerConfig);
 }