tests : add script to benchmark whisper.cpp on LibriSpeech corpus (#2999)

* tests : add script to benchmark whisper.cpp on LibriSpeech corpus

LibriSpeech is a widely-used benchmark dataset for training and
testing speech recognition models.

This adds a set of scripts to measure the recognition accuracy of
whisper.cpp models, following the common benchmark standards.

Signed-off-by: Fujimoto Seiji <fujimoto@ceptord.net>

* Document how to prepare `whisper-cli` and model files

Feedback from Daniel Bevenius.

This adds a short code example how to prepare the `whisper-cli`
command, to make the initial setup step a little bit clearer.

Signed-off-by: Fujimoto Seiji <fujimoto@ceptord.net>

* tests : Simplify how to set up Python environment

Based on a feedback from Georgi Gerganov.

Instead of setting up a virtual environment in Makefile, let users
set up the Python environment. This is better since users may have
their own preferred workflow/toolkit.

Signed-off-by: Fujimoto Seiji <fujimoto@ceptord.net>

---------

Signed-off-by: Fujimoto Seiji <fujimoto@ceptord.net>

tests/librispeech/README.md

@@ -0,0 +1,60 @@
+# whisper.cpp/tests/librispeech
+
+[LibriSpeech](https://www.openslr.org/12) is a standard dataset for
+training and evaluating automatic speech recognition systems.
+
+This directory contains a set of tools to evaluate the recognition
+performance of whisper.cpp on LibriSpeech corpus.
+
+## Quick Start
+
+1. (Pre-requirement) Compile `whisper-cli` and prepare the Whisper
+   model in `ggml` format.
+
+   ```
+   $ # Execute the commands below in the project root dir.
+   $ cmake -B build
+   $ cmake --build build --config Release
+   $ ./models/download-ggml-model.sh tiny
+   ```
+
+   Consult [whisper.cpp/README.md](../../README.md) for more details.
+
+2. Download the audio files from LibriSpeech project.
+
+   ```
+   $ make get-audio
+   ```
+
+3. Set up the environment to compute WER score.
+
+   ```
+   $ pip install -r requirements.txt
+   ```
+
+   For example, if you use `virtualenv`, you can set up it as follows:
+
+   ```
+   $ python3 -m venv venv
+   $ . venv/bin/activate
+   $ pip install -r requirements.txt
+   ```
+
+4. Run the benchmark test.
+
+   ```
+   $ make
+   ```
+
+## How-to guides
+
+### How to change the inferece parameters
+
+Create `eval.conf` and override variables.
+
+```
+WHISPER_MODEL = large-v3-turbo
+WHISPER_FLAGS = --no-prints --threads 8 --language en --output-txt
+```
+
+Check out `eval.mk` for more details.