Update README.md

README.md

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----
-license: apache-2.0
----
+---
+license: apache-2.0
+tags:
+- Embeddings
+- ACAV100M
+- AE29H_float32
+- nanowakeword
+- noice
+---
+
+# AE29H_float32
+
+**Audio Embeddings ~29 hours** dataset contains **precomputed audio embeddings** designed for training **NanoWakeWord** models. The embeddings are intended to be used as **general-purpose negative training data**, meaning the audio does **not contain the target wake word or phrase**.
+
+Unlike raw audio datasets, the files in this dataset contain **low-dimensional audio embeddings** extracted from audio clips using a pre-trained speech embedding model. These embeddings can be directly used as input features when training wake-word detection models with NanoWakeWord.
+
+The goal of this dataset is to provide **diverse background audio representations** (speech, environmental noise, music, etc.) that help wake-word models learn to avoid false activations.
+
+---
+
+# Dataset Source
+
+The embeddings were generated from a subset of the **ACAV100M** dataset.
+
+ACAV100M is a very large automatically curated audio-visual dataset created from millions of internet videos and designed for large-scale audio-visual learning. It contains diverse real-world audio such as speech, environmental sounds, music, and background noise.
+
+For this dataset:
+
+* A **20K subset (~2 days of audio)** from ACAV100M.
+* Audio clips were processed and converted into embeddings suitable for wake-word training.
+
+---
+
+# Dataset Statistics
+
+* **Shape:**
+
+  ```
+  (21115, 16, 96)
+  ```
+
+* **Total samples:**
+  **21,115**
+
+* **Feature dimensions:**
+  * **Embedding size:** 96
+
+
+---
+
+# Data Type
+
+```
+dtype: float32
+```
+
+**Value range**
+
+```
+min: -77.23914
+max: 95.59355
+```
+
+---
+
+# Intended Use
+
+This dataset is intended for:
+
+* Training **NanoWakeWord wake-word detection models**
+* Providing **negative training examples**
+* Improving **false-positive robustness**
+* Training models that operate directly on **audio embeddings**