Datasets:

Codyfederer
/

test6

text stringlengths 10 351	speaker_id stringclasses 3 values	emotion stringclasses 17 values	language stringclasses 1 value
What we need to do is to get the students to understand that they can go out and do things that are not in their own hands.	speaker_0	neutral	en
Hello, you're listening to The Science of Everything podcast, episode 145.	speaker_0	neutral	en
Relativity and black Holes.	speaker_0	interest	en
I'm your host, James Fodor.	speaker_0	neutral	en
This episode is a continuation of the discussion of general relativity, which we began in episode...	speaker_0	neutral	en
136, which is the prerequisite for this episode.	speaker_0	neutral	en
In that episode, we talked about general relativity and explained the notion of space-time, and how we describe velocity, distance and curvature of space-time using mathematical formalisms.	speaker_0	interest	en
And how we combine these formalisms together.	speaker_0	neutral	en
To yield Einstein's field equations, which loosely say that, the curvature of space-time.	speaker_0	neutral	en
Is proportional to the energy and matter content of spacetime.	speaker_0	neutral	en
And I explained how Einstein's field equations are a series of 10.	speaker_0	neutral	en
Coupled nonlinear partial differential equations.	speaker_0	neutral	en
Which means that they're very complex and difficult to solve.	speaker_0	neutral	en
For any realistic cases.	speaker_0	neutral	en
However, I did say that there are some closed form, meaning sort of simply mathematically describable.	speaker_0	neutral	en
Solutions known.	speaker_0	neutral	en
To Einstein's field equations, and I'll talk about them in a future episode.	speaker_0	interest	en
Well, now is that future episode, or.	speaker_0	neutral	en
One of those future episodes where we'll talk about solutions to Einstein's field equations, and in particular, in this episode, we're going to focus on the Schwarzschild metric.	speaker_0	interest	en
And how it's able to describe Well.	speaker_0	neutral	en
Described the existence of black holes.	speaker_0	interest	en
So we'll talk about deriving the Schwarzschild metric, how to interpret the resulting metric.	speaker_0	interest	en
And then we'll see how.	speaker_0	neutral	en
Z resulting metric.	speaker_0	neutral	en
Yields predictions which have been experimentally verified and thereby serving as experimental evidence in favour of general relativity.	speaker_0	interest	en
We'll then talk in more detail about Schwarzschild black holes.	speaker_0	neutral	en
Some of the phenomena there, like the event horizon, singularity and so forth.	speaker_0	interest	en
And we'll conclude by discussing some of the unsolved problems or outstanding issues with black holes, including the phenomena of hawking radiation, the no-hair theorem, and the black hole information Paradox.	speaker_0	interest	en
This will be a pretty dense episode, so hope you're ready.	speaker_0	neutral	en
And let's then jump into it.	speaker_0	neutral	en
But bear in mind, though, I will be assuming...	speaker_0	neutral	en
That you've listened to.	speaker_0	neutral	en
On general relativity, because that introduces some of the key ideas that I'll...	speaker_0	interest	en
We'll start with exactly where we picked up last time, which is Einstein's Field equations, a series of 10, coupled, nonlinear, partial differential equations relating the curvature of space and time to the energy and matter content of space and time.	speaker_0	interest	en
What we're going to do is try to find a solution to these equations.	speaker_0	neutral	en
There are a number of closed form solutions known.	speaker_0	neutral	en
We're going to focus on one of them today.	speaker_0	neutral	en
And essentially, what this amounts to is solving for the equations to find the metric.	speaker_0	neutral	en
Mathematical description of the overall shape of space and time.	speaker_0	interest	en
A metric that satisfies the equations.	speaker_0	neutral	en
So the term on the left of the equations is the Einstein tensor.	speaker_0	neutral	en
Denoted as a capital, G.	speaker_0	neutral	en
And it more or less describes the curvature of the metric.	speaker_0	neutral	en
Which represents the structure of space and time.	speaker_0	neutral	en
On the right hand side is the stress energy tensile, which describes the energy content of of space and time.	speaker_0	neutral	en
There's sort of two ways to solve.	speaker_0	neutral	en
These couple of equations.	speaker_0	neutral	en
One is to postulate a stress energy tensor, so to stipulate what the energy content of space is, and then solve for the metric.	speaker_0	neutral	en
Given далее energy content.	speaker_0	neutral	en
You can start with the metric.	speaker_0	neutral	en
So specify what, though.	speaker_0	neutral	en
And then solve for the stress energy tensor that will give you that metric.	speaker_0	neutral	en
So in this particular case, the way we're going to do it, is we're going to stipulate what the stress-energy tensor is.	speaker_0	neutral	en
As well as making a few other assumptions.	speaker_0	neutral	en
And then we're going to see what metric that gives us, what metric satisfies.	speaker_0	interest	en
The equations when we stipulate what the energy content of the universe is.	speaker_0	neutral	en
So we're going to stipulate at the outset that the energy and matter content of the universe, or at least the region of the universe that we're considering.	speaker_0	neutral	en
Is going to be zero.	speaker_0	neutral	en
So we're looking for a vacuum solution, it's often called, an empty space solution of the equation.	speaker_0	neutral	en
So obviously that simplifies things dramatically.	speaker_0	neutral	en
Because the right hand side of the equation is just zero.	speaker_0	neutral	en
And it the equation, simplified down to the the rishi tends, is equal to zero.	speaker_0	neutral	en
Remember, basically describes the curvature.	speaker_0	neutral	en
Of um space of time in that region.	speaker_0	neutral	en
So the next step, now that we've already simplified things quite a lot, is to make further assumptions to help simplify things.	speaker_0	neutral	en
The next thing that we're going to assume is that the Rishi Tensor, or all of the components of the Rishi Tensor, are independent of time, so they're static.	speaker_0	neutral	en
They're constant over time.	speaker_0	neutral	en
So this is just representing the type of solution that we're looking for, which is a static solution.	speaker_0	neutral	en
Again, this is often done for simplicity.	speaker_0	neutral	en
Now it turns out, when you make this assumption, this dramatically simplifies things further.	speaker_0	neutral	en
Because it means that any terms that interact with the time coordinate, Remember, there's four coordinates.	speaker_0	neutral	en
Of, of space and time.	speaker_0	neutral	en
There's one time coordinate and three spatial coordinates.	speaker_0	neutral	en
So any of them that interact with the time coordinate have to go to zero.	speaker_0	neutral	en
There will be changes over time.	speaker_0	neutral	en
Making this assumption of a static field means that instead of having 16 components, of the Rishi Tensor, now there are only going to be four components.	speaker_0	neutral	en
And they're just the diagonal components.	speaker_0	neutral	en
So those along the diagonal.	speaker_0	neutral	en
A 4x4 matrix is only the ones along the diagonal.	speaker_0	neutral	en
That will be non-zero, everything else goes to zero.	speaker_0	neutral	en
When we make this assumption of a static field.	speaker_0	neutral	en
Things are now very simple because instead of having these 10...	speaker_0	neutral	en
Coupled partial, different, nonlinear, partial, differential equations.	speaker_0	neutral	en
Now we've got, we've reduced it down to four much simpler equations.	speaker_0	neutral	en
All of which are just equal to zero.	speaker_0	neutral	en
Four equations for each, essentially one for each of the coordinates, a one-time equation.	speaker_0	neutral	en
And one for each of the three spatial coordinates.	speaker_0	neutral	en
Now, to make even more simplifications, we introduce a third assumption, which is that we're going to look for a spherically symmetrical solution.	speaker_0	neutral	en
So we're kind of interested in solutions that look the same, when you rotate them.	speaker_0	interest	en
That simplifies things a lot further because now we only have to worry essentially about two Coordinates.	speaker_0	neutral	en
The radius, which is the distance from the center.	speaker_0	neutral	en
And then one angle coordinate.	speaker_0	neutral	en
Even with all of these simplifications, the equations that we have to solve are still somewhat complicated.	speaker_0	confusion	en
But the algebra is at least now solvable, and obviously I can't go through all the details here.	speaker_0	neutral	en
But at this point, what we need to do is take the highly simplified form of the Rishi tensor that we've derived by making these assumptions.	speaker_0	neutral	en
And then just substitute in for the actual form of the Rishitensa.	speaker_0	neutral	en
Remember, the Rishitensa is defined in terms of mathematical objects called Christoffel symbols.	speaker_0	neutral	en
Basically, describe the way in which our path changes, owing to the curvature of space as we move, remember, in the last episode, we talked about the idea of someone holding a spear out in front of them?	speaker_0	interest	en
And starting at the North Pole and walking down towards the equator.	speaker_0	neutral	en
Their spear will change direction as they walk along, even if they, it doesn't.	speaker_0	neutral	en

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test6

This is a merged speech dataset containing 1994 audio segments from 2 source datasets.

Dataset Information

Total Segments: 1994
Speakers: 3
Languages: en
Emotions: neutral, negative_surprise, positive_surprise, distress, relief, contentment, adoration, interest, confusion, happy, sadness, triumph, fear, disappointment, awe, realization, angry
Original Datasets: 2

Dataset Structure

Each example contains:

audio: Audio file (WAV format, 16kHz sampling rate)
text: Transcription of the audio
speaker_id: Unique speaker identifier (made unique across all merged datasets)
emotion: Detected emotion (neutral, happy, sad, etc.)
language: Language code (en, es, fr, etc.)

Usage

Loading the Dataset

from datasets import load_dataset

# Load the dataset
dataset = load_dataset("Codyfederer/test6")

# Access the training split
train_data = dataset["train"]

# Example: Get first sample
sample = train_data[0]
print(f"Text: {sample['text']}")
print(f"Speaker: {sample['speaker_id']}")
print(f"Language: {sample['language']}")
print(f"Emotion: {sample['emotion']}")

# Play audio (requires audio libraries)
# sample['audio']['array'] contains the audio data
# sample['audio']['sampling_rate'] contains the sampling rate

Alternative: Load from CSV

import pandas as pd
from datasets import Dataset, Audio, Features, Value

# Load the CSV file
df = pd.read_csv("data.csv")

# Define features
features = Features({
    "audio": Audio(sampling_rate=16000),
    "text": Value("string"),
    "speaker_id": Value("string"),
    "emotion": Value("string"),
    "language": Value("string")
})

# Create dataset
dataset = Dataset.from_pandas(df, features=features)

Dataset Structure

The dataset includes:

data.csv - Main dataset file with all columns
*.wav - Audio files in the root directory
load_dataset.txt - Python script for loading the dataset (rename to .py to use)

CSV columns:

audio: Audio filename (in root directory)
text: Transcription of the audio
speaker_id: Unique speaker identifier
emotion: Detected emotion
language: Language code

Speaker ID Mapping

Speaker IDs have been made unique across all merged datasets to avoid conflicts. For example:

Original Dataset A: speaker_0, speaker_1
Original Dataset B: speaker_0, speaker_1
Merged Dataset: speaker_0, speaker_1, speaker_2, speaker_3

Original dataset information is preserved in the metadata for reference.

Data Quality

This dataset was created using the Vyvo Dataset Builder with:

Automatic transcription and diarization
Quality filtering for audio segments
Music and noise filtering
Emotion detection
Language identification

License

This dataset is released under the Creative Commons Attribution 4.0 International License (CC BY 4.0).

Citation

@dataset{vyvo_merged_dataset,
  title={test6},
  author={Vyvo Dataset Builder},
  year={2025},
  url={https://huggingface.co/datasets/Codyfederer/test6}
}

This dataset was created using the Vyvo Dataset Builder tool.

Downloads last month: 356

Size of downloaded dataset files:

394 kB

Size of the auto-converted Parquet files:

242 MB

Number of rows:

1,994