chore: import upstream snapshot with attribution

docs/source/asr/speech_classification/intro.rst

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+Speech Classification
+==================================
+Speech Classification refers to a set of tasks or problems of getting a program to automatically classify input utterance or audio segment into categories, 
+such as Speech Command Recognition (multi-class), Voice Activity Detection (binary or multi-class), and Audio Sentiment Classification (typically multi-class), etc.
+
+**Speech Command Recognition** is the task of classifying an input audio pattern into a discrete set of classes. 
+It is a subset of Automatic Speech Recognition (ASR), sometimes referred to as Key Word Spotting, in which a model is constantly analyzing speech patterns to detect certain "command" classes. 
+Upon detection of these commands, a specific action can be taken by the system. 
+It is often the objective of command recognition models to be small and efficient so that they can be deployed onto low-power sensors and remain active for long durations of time.
+
+
+**Voice Activity Detection (VAD)** also known as speech activity detection or speech detection, is the task of predicting which parts of input audio contain speech versus background noise.
+It is an essential first step for a variety of speech-based applications including Automatic Speech Recognition. 
+It serves to determine which samples to be sent to the model and when to close the microphone.
+
+**Spoken Language Identification (Lang ID)** also known as spoken language recognition, is the task of recognizing the language of the spoken utterance automatically.
+It typically serves as the prepossessing of ASR, determining which ASR model would be activate based on the language. 
+
+
+The full documentation tree is as follows:
+
+.. toctree::
+   :maxdepth: 8
+
+   models
+   datasets
+   results
+   configs
+   resources.rst
+
+.. include:: resources.rst