Fix typo in speech synthesis readme

Spectrograms are acoustic features rather than linguistic features.

Author: vinhngx

PyTorch/SpeechSynthesis/README.md

@@ -15,7 +15,7 @@ In this collection, we will cover:
 TTS synthesis is a 2-step process described as follows:
 
 1. Text to Spectrogram Model:
-This model Transforms the text into time-aligned features such as spectrogram, mel spectrogram, or F0 frequencies and other linguistic features. We use architectures like Tacotron
+This model Transforms the text into time-aligned features such as spectrogram, mel spectrogram, or F0 frequencies and other acoustic features. We use architectures like Tacotron
 
 2. Spectrogram to Audio Model:
 Converts generated spectrogram time-aligned representation into continuous human-like audio—for example, WaveGlow.
@@ -51,4 +51,4 @@ Here are the examples relevant for image segmentation, directly from [Deep Learn
 
 2. FastPitch for text to melspectogram generation using PyTorch
 - [Git repository](https://github.com/NVIDIA/DeepLearningExamples/tree/master/PyTorch/SpeechSynthesis/FastPitch)
-- Uses PyTorch 20.03-py3 [NGC container](https://ngc.nvidia.com/registry/nvidia-pytorch)
+- Uses PyTorch 20.03-py3 [NGC container](https://ngc.nvidia.com/registry/nvidia-pytorch)