SSM-AST: State Space Models for Automatic Speech Transcription

This repository contains model artifacts for the master's thesis β€œState Space Models for Automatic Speech Transcription.” It provides the trained acoustic encoder checkpoints, language-model checkpoints, n-gram training text, and selected training logs used to support evaluation of a pure State Space Model (SSM) automatic speech transcription pipeline on LibriSpeech.

The code for training and evaluation is maintained separately. This Hugging Face repository is intended as a checkpoint and artifact archive so that the thesis evaluation pipeline can be run without retraining the full models from scratch.

Repository contents

SSM-AST/
β”œβ”€β”€ datasets/
β”‚   └── librispeecm_lm_dataset_pre-processed_char_level_text.txt
β”œβ”€β”€ encoder_checkpoints/
β”‚   β”œβ”€β”€ enc_mamba3_460h_checkpoint_best_epoch=49_val_wer=0.255.ckpt
β”‚   β”œβ”€β”€ enc_mamba3_960h_checkpoint_best_epoch=91_val_wer=0.186.ckpt
β”‚   β”œβ”€β”€ enc_mamba_460h_checkpoint_best_epoch=49_val_wer=0.227.ckpt
β”‚   β”œβ”€β”€ enc_mamba_960h_checkpoint_best_epoch=100_val_wer=0.155.ckpt
β”‚   β”œβ”€β”€ enc_ssssm_460h_checkpoint_best_epoch=49_val_wer=0.197.ckpt
β”‚   β”œβ”€β”€ enc_ssssm_960h_checkpoint_best_epoch=100_val_wer=0.111.ckpt
β”‚   └── enc_ssssm_960h_checkpoint_best_epoch=98_val_wer=0.111.ckpt
β”œβ”€β”€ lm_checkpoints/
β”‚   β”œβ”€β”€ lm_mamba3_checkpoint_MaxChars-1000000000_ds-64_d320_L18.pt
β”‚   β”œβ”€β”€ lm_mamba_checkpoint_MaxChars-1000000000_d320_L18.pt
β”‚   └── lm_ngram_checkpoint_char_10gram.pkl
β”œβ”€β”€ log files/
β”‚   β”œβ”€β”€ 0utput_exp-mamba-1_960h_W-320_D-48_S-16_B-128_E-100.txt
β”‚   β”œβ”€β”€ 0utput_exp-mamba3_460h_W-512_D-30_S-16_B-64_E-50.txt
β”‚   β”œβ”€β”€ 0utput_exp-mamba3_enc_960h_W-320_D-48_S-16_b-64_E-100.txt
β”‚   β”œβ”€β”€ 0utput_exp-mamba_dt_bias_hier_460h_W-512_D-30_S-16.txt
β”‚   β”œβ”€β”€ 0utput_exp-v75_460h_hier_gating_256_42.txt
β”‚   β”œβ”€β”€ 0utput_exp-v77_960h_hier_gating_320_48.txt
β”‚   β”œβ”€β”€ mamba3_elm_training.log
β”‚   └── mamba_elm_training.log
β”œβ”€β”€ .gitattributes
└── README.md
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